Student Handbook A.Y.2018-19/I Sem

IV-B.Tech STUDENT HANDBOOK A.Y.2018-19/I SEM

Department of CSE

MARRI LAXMAN REDDY INSTITUTIONS

MLR Institute of Technology Dundigal (V), Quthbullapur (M), R.R Dist, Hyderabad – 500043, A.P www.mlrinstitutions.ac.in

VISION STATEMENT

VISION OF THE DEPARTMENT Promote Innovation-centric education to produce globally competent graduates in Computer Science and Engineering education & research capable of building a strong and developed nation.

MISSION STATEMENT

MISSION OF THE DEPARTMENT M1: Provide rigorous course work and State-of-the-Art laboratories for the students to make them globally competent. M2: Strengthen the department interaction with Multi National Companies to enhance graduate technological advancement skills and research capabilities. M3: Impart human values and ethics to the graduates for serving the society with highest regard to the mother land.

Program Educational Objectives (PEOs): PEO1: Graduates of the program will have a globally competent professional career in software Industry.

PEO2: Graduates of the program will pursue higher education and research.

PEO3: Graduates of the program will have entrepreneur skills to solve societal problems.

Our Pioneers…

Marri Laxman Reddy- Chairman Sri Marri Laxman Reddy is a man of vision, values and beliefs. He is a firm believer, that an educated nation is a prosperous nation. He is also a veteran international athlete. He strongly encourages students to participate in sports. He believes that sports build self-esteem, confidence and motivation in students. With sports, students can recognize the ways and benefits of goal setting and practice. This in turn helps them to excel academically and build up their social skills. We are enchanted to have such an inspiring personality among us. As a sportsman and academician, he had battled against all odds and reached the pinnacle of success. Not only a man of words, he is also a man of deeds. He is highly passionate about uplifting the down trodden, alleviate ignorance by conducting awareness among people. Undoubtedly, he is a living proof and exemplar of humanity. His selfless services to the field of education are noteworthy.

MARRI RAJASEKHAR REDDY – SECRETARY Mr. Marri Raja Shekar Reddy is the mentor of MLR Institute of Technology and a man of remarkable abilities and great acumen. His good will, appreciation, motivation and positive vibration has a great impact in moulding the students. He extends unconditional support and tremendous help to the students to achieve their goals. His proactive hard-work and dedication has taken the institute to the zenith of excellence. He strives hard to initiate various industry oriented programs for the benefit of the students and he envisions his students to be present at the top most position in the industry.

Dr.K.SRINIVAS RAO – PRINCIPAL Dr. K. Srinivas Rao, has been serving the noblest of the professions with great devotion from the past 20 years. He proves himself as a special leader by the equality of his action and integrity of his intent. The courage to make tough decisions and the compassion to listen to the need of others is an art of our Principal. It is his sense of commitment which creates an apt platform for the staff and the students to grow academically, mentally and spiritually. He believes that students should inculcate not only academic qualifications but also qualities like leadership, teamwork, determination, confidence, self -belief, respect and consideration. He looks forward for the betterment of the students and constantly extends his support in all the high prospects of our institution..

TABLE OF CONTENTS

S.No. Content Page No. 1. General Information About the college 1.0.Beautiful campus 1.1.Autonomous status 1.2.Performance 1 1.3.Faculty 1.4.Infrastructure 1.5.Laboratories 1.6.CAT Centre 1.7.English Language Laboratory 1.8.R&D Cell 1.9.Library 1.10.National Programme on Technology 2 Enhanced Learning (NPTEL) 1.11.Co-Curricular Activities 1.12.Professional bodies 1.13.Extra curricular activities 1.14.In House projects 3 1.15.MOUs 1.16.Student achievements 4 1.17.Alumni Outreach 5 1.18.Contact information 2. Placement and Higher Studies 2.1.Industry Grade skills required for Employment 2.2.Important criteria for employment 6 2.3.Higher Studies 2.4.Various Scholarships available in India 2.5.Various International Scholarships available in India 3. Student Career Oriented Professional Certification Courses 7 3.1 Help Desk 4. Performance Monitoring and Guidance 4.1. Student Feedback 4.2.Class Teacher 4.3.Class Representatives and their roles 8 4.4. Performance Counseling 4.5. Remedial Classes / Tutorial / Revisions 4.6. Backlog Management 4.7. Correspondence with Parents 5. Rules & Regulations for students 5.1. Administrative 5.2. Academic 5.3. Dress Code 5.4. Discipline & Punctuality 9 5.5. Lab Classes 5.6. Fee 5.7. Transport 5.8. Library Rules 5.9. General 5.10. Ragging

6. Academic Regulations (MLR-17 AUTONOMOUS) 6.1. Award of B.Tech. Degree 10 6.2. 6.3. Credits 6.4. Distribution and Weightage of marks 6.5. Attendance Requirements 11 6.6. Minimum Academic Requirements 12 7. Course Calendar for the Year 1

8. B.Tech. III Year Course Structure (R16) 2 9. CRYPTOGRAPHY & NETWORK SECURITY

9.0 COURSE DESCRIPTION 9.1. COURSE OVERVIEW 9.2. PREREQUISITE(S): 9.3. CMARKS DISTRIBUTION 9.4. EVALUATION SCHEME COURSE OBJECTIVES 13 9.5. COURSE OUTCOMES 9.6 HOW PROGRAM OUTCOMES ARE ASSESSED: 9.7. SYLLABUS: 9.8 COURSE PLAN: 9.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 9.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 9.11 OBJECTIVE QUESTIONS: 9.12 TUTORIAL QUESTION BANK 9. 13 ASSIGNMENT QUESTIONS: 10. CLOUD COMPUTING

10.0 COURSE DESCRIPTION 10.1. COURSE OVERVIEW 10.2. PREREQUISITE(S): 10.3. MARKS DISTRIBUTION 10.4. EVALUATION SCHEME COURSE OBJECTIVES 10.5. COURSE OUTCOMES 14 10.6 HOW PROGRAM OUTCOMES ARE ASSESSED: 10.7. SYLLABUS: 10.8 COURSE PLAN: 10.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 10.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 10.11 OBJECTIVE QUESTIONS: 10.12 TUTORIAL QUESTION BANK 10. 13 ASSIGNMENT QUESTIONS:

15 11. DATA MINING & WAREHOUSING 11.0 COURSE DESCRIPTION 11.1. COURSE OVERVIEW 11.2. PREREQUISITE(S): 11.3. MARKS DISTRIBUTION 11.4. EVALUATION SCHEME COURSE OBJECTIVES 11.5. COURSE OUTCOMES 11.6 HOW PROGRAM OUTCOMES ARE ASSESSED: 11.7. SYLLABUS:

11.8 COURSE PLAN: 11.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 11.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 11.11 OBJECTIVE QUESTIONS: 11.12 TUTORIAL QUESTION BANK 11. 13 ASSIGNMENT QUESTIONS:

16 12. BIG DATA ANALYTICS 12.0 COURSE DESCRIPTION 12.1. COURSE OVERVIEW 12.2. PREREQUISITE(S): 12.3. MARKS DISTRIBUTION 12.4. EVALUATION SCHEME COURSE OBJECTIVES 12.5. COURSE OUTCOMES 12.6 HOW PROGRAM OUTCOMES ARE ASSESSED: 12.7. SYLLABUS: 12.8 COURSE PLAN: 12.9 M APPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 12.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 12.11 OBJECTIVE QUESTIONS: 12.12 TUTORIAL QUESTION BANK 12. 13 ASSIGNMENT QUESTIONS: 17 13. SOFTWARE TESTING FUNDAMENTALS 13.1. COURSE OVERVIEW 13.2. PREREQUISITE(S): 13.3. MARKS DISTRIBUTION 13.4. EVALUATION SCHEME COURSE OBJECTIVES 13.5. COURSE OUTCOMES 13.6 HOW PROGRAM OUTCOMES ARE ASSESSED: 13.7. SYLLABUS:

13.8 COURSE PLAN: 13.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 13.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: 13.11 OBJECTIVE QUESTIONS: 13.12 TUTORIAL QUESTION BANK 13. 13 ASSIGNMENT QUESTIONS: 18 14. CRYPTOGRAPHY & NETWORK SECURITY LAB 14.1. SYLLABUS:

14.2 Lab Schedule 19 15 CLOUD COMPUTING LAB 15.1.Syllabus

15.2.Lab Schedule 20 16. DATAMING AND WAREHOUSING LAB 16.1.Syllabus 16.2.Lab Schedule

MLR Institute of Technology Dundigal, Quthbullapur Mandal, R.R. Dist.- 500 043. Ph: 08418 – 204066, 204088, 9866755166

1.GENERAL INFORMATION

ABOUT THE COLLEGE

1.0 BEAUTIFUL CAMPUS: Set in Sylvan surroundings away from the hustle & bustle of city life yet only 4 km away from Mahindra Satyam Technology Park on Balanagar – Narsapur state highway, the Institute is extremely conducive to academic, co-curricular and extra-curricular activities. It has large and well ventilated buildings with modern equipment in place and “State of the art”, sports facilities.

HIGHLIGHTS:

1.1 AUTONOMOUS STATUS MLR Institute of Technology is now an Autonomous Institution!! Under the UGC Autonomous College Scheme for a period of Six Years

1.2 PERFORMANCE The college has been AA rated under colleges in AP by Careers360 magazine. Also, the college has been ranked at 126 by the week magazine in the Best colleges Survey-2013.

1.3 FACULTY: The College is proud to have the best faculty, a blend of experienced and academics with eminent academicians team IIT’s, NIT’s and other reputed organizations teaching at the Institute that makes MLRIT as one of the best Institute pursue B.Tech, M.Tech,MCA and MBA as one of the under JNTU Hyderabad. The faculty is constantly encouraged to upgrade their qualifications and a number of them have enrolled for Ph.D. Most of the faculty members have been empowered with High Impact teaching under Wipro Mission 10X program.

1.4 INFRASTRUCTURES:  Spacious campus and natural surroundings with plenty of greenery  College Transport facilities from twin cities for students and staff from all corners of the city  Air Conditioned auditorium for organizing events, workshops and seminars  Good Canteen facility  HDFC Bank ATM in the campus  Fully equipped Laboratories with the state-of-art equipments

1.5 LABORATORIES: The Institute has State of the art laboratories with 1000 plus Branded Systems equipped with latest hardware and software with online testing facility catering to the needs of CSE, IT. The Institute also has well equipped Electronic Labs, Aeronautical Engineering Labs and Workshops for ECE and Aeronautical Engineering Students. The college has recently established Microsoft, IBM for CSE/IT cadence lab for VLSI design and CATIA Aeronautical Design Lab.

1.6 CAT Centre: The Institute is an Authorized IIM Cat Centre, which will conduct tests all through the year as per the IIM schedule.

1.7 ENGLISH LANGUAGE LABORATORY: The Institute has established Ultramodern Computerized English language Laboratory with 60 plus Computer Systems loaded with latest Software to enhance the Softskills of Students to make the Students Industry ready. The Library also have the previous University Exam Question papers and previous project reports from all the departments. The library contains recorded lectures of all IIT professors from NPTEL.

1.8 R&D Cell: The Institute has an R&D Cell under the Chairmanship of Dr Karthik Rajendra. The R&D cell undertakes externally funded R&D projects from agencies like AICTE, DST, UGC and other similar state, private and society / trust bodies. It also undertakes research publications and interactions of faculty members with outside world.

1.9 LIBRARY: The Institute Library has over 29000 books and 244 National and International journals and 15 Magazines that are required to all branches of Engineering. The Institute has the unique distinction of becoming Member of DELNET, Infotrac engineering online journals that connects more than 700 libraries in Asia Pacific Region. The Library has 35 Computers with 10 MB PS, Internet Facility that makes our knowledge Savvy Students to be technically competent on par with Industry professionals. NPTEL Videos and e-books, MIT courses also available.

1.10 National Programme on Technology Enhanced Learning (NPTEL) The main objective of NPTEL program is to enhance the quality of engineering education in the country by developing curriculum based video and web courses. This is being carried out by seven IITs and IISc Bangalore as a collaborative project. In the first phase of the project, supplementary content for 129 web courses in engineering / science and humanities have been developed. Each course contains materials that can be covered in depth in 60 or more lecture hours. In addition, 110 courses have been developed in video format, with each course comprising of approximately 60 or more one-hour lectures. In the next phase other premier institutions are also likely to participate in content creation.

1.11 Co-Curricular Activities: The Institution organizes Local Industrial Visits to Organizations like DOORDARSHAN, BSNL, and to Student Conferences like HYSEA,Student Conference at INFOSYS, Gachibowli Campus, and Government Sponsored Summits like INDO SOFT IT Summit at Hitex City Convention Centre to Interface with the Industry for Career Planning and to make them Industry Ready. The Institute focuses on Techno Management Events like Technonium and Zavtra to enhance the Technical Skills and Soft Skills to make them Employable.

1.12 Professional Bodies: MLR Institute of Technology has the unique distinction of becoming Institutional Member in Professional bodies such as Confederation of Indian Industry (CII), Aeronautical Society of India (AeSI), Computer Society of India (CSI), Institute of Electronics and Telecommunication Engineering (IETE), Indian Society of Technical Education (ISTE), ELIAP and Hyderabad Management Association.(HMA)

1.13 Extra-Curricular Activities:  MLRIT has State of the art facilities like Olympic Style Basketball Court, Volleyball Court, Gymnasium, Indoor Stadium, Cricket Stadium with Lush Green Outfields and 400 meter excellent track for Athletic meet. MLR Institute of Technology has been regularly conducting JNTU Zonal Games and Annual Open Invitational Volleyball, Football, Cricket Tournaments.  The Institute also organizes various Cultural Events like Traditional Day for freshers, “ZAVTRA” A National Level Technical Fest, TRISHNA - The Annual Day Celebrations, ECSTASY – A Cultural Nite by Vishal & Shekhar, Indian Idol Sri Ram, Farewell Party for final year students, Alumni Meet for Ex. Students and Graduation Day for graduated students every year to imbibe a spirit of Oneness.

NSS Activities: A Sense of social responsibility is inculcated in Young Minds by organizing Plantation Programmes, Health Awareness Camps, Blood Donation Camps, Flood Relief Camps, Distribution of Books to School Children under Digital Literacy Programme of Microsoft by MLRIT NSS Volunteers.

1.14 In House Projects: The students are taking part in International Project competitions hosted by major MNCs, like IBM, Microsoft and Infosys. The Great Mind Challenge hosted by IBM, Microsoft Imagine Cup and project work as part of foundation programme conducted under the aegis of Infosys are some of the important projects presently being undertaken by the students of MLRIT. Further, the students are encouraged to do In House Projects under the supervision of expect faculty members.In addition,students are encouraged to give innovative ideas and do projects under the aegis of Microsoft academic innovative alliance.

1.15 MOUs:  BOEING  Tech Mahindra  Infotech Enterprises Ltd.  IBM  Oracle  Sun Microsystems  Infosys  CA Labs  Tata Advanced Systems  Microsoft  Globarena  Wipro  IUCEE For giving special training programmes to engineering students and Faculty members of the institute

1.16 Student Achievements:  Our College students got 2nd Place out of 2100 colleges in E-Plus Challenge 14 conducted by The Hindu in Hyderabad in March 2014.  MLR Institute of Technology students have been securing JNTUH ranks regularly right from 1st batch itself, reflecting the core competencies of the faculty and dedicated efforts of the students.  Mr Venkata Rama Varma student of 3rd year Aero has participated and stood 3rd in National Aero-Modeling competition conducted by Boeing held during Techfest 2014 at IIT Madras.  Mr. Venkata Rama Varma student of 3rd year Aero has participated and stood 3rd in Avion- E and Hower Mania held during Techfest 2013 at NIT Warangal.  Mr Venkata Rama Varma and NAM Sai Teja students of 3rd year Aero have been selected for Boeing National Aeromodeling Competition which will be held at IIT Delhi next Month.  Mr. Venkata Rama Varma student of 3rd year Aero has participated and stood 1st in Aero- Modeling Competition held during Techfest 2013 at Christ University  Mr Venkata Rama Varma student of 3rd year Aero has participated and stood 3rd in Blitz Krieg Design Challenge held during Techfest 2013 at IIT BOMBAY.  Mr.Varma and team III-Aeronautical students got 2nd Prize in ICRAMAV-2013 organized by JNTUH for their MAV (Micro Aerial Vehicle).  Mr.Eshwer Reddy student of 4th year Aero has participated and stood 2nd Prize in Working Models competition organized by Rotary Club.  Three of 2nd Aero students got Rs. 5000/- cash prize in Design Competition organized Engineers CAD Centre Hyderabad

1.17 Alumni Outreach  The Institute has Alumni Association under the name and Style of MLR Alumni Association and conducted the First Alumni Meet on 14th Feb 2009 with the first batch 0f 2008 passed out MBA students attending the meet.  The Association has honoured the 2009 batch B.Tech, MCA along with MBA students by conducting the Second Alumni Meet at hotel Blue Fox on 13th March 2010 where more than 200 students participated in the Meet.  The Association conducted 3rd Alumni meet for 2010 batch B.Tech, MCA & MBA students on 16th April 2011 at our college Auditorium.  The Association conducted 4th Alumni meet for 2011 batch B.Tech, MCA & MBA students on 14th July 2012 at our college Auditorium.  The Association conducted 5th Alumni meet for 2012 batch B.Tech & MBA students on 11th May 2013 at our college Auditorium.  The Association conducted 6th Alumni meet for 2013 batch B.Tech, M.Tech & MBA students on 14th Feb 2015 at our college Auditorium.

1.18 Contact Information Principal - Dr.K.Srinivasa Rao - 9959656448 Dean (CS) - Prof. K. L. Chugh - 9866666601 Department Head CSE - Dr.N.Chandra Sekhar Reddy - 9618880606 Department Head IT - Dr.G.Kiran Kumar - 9542333391 Department Head ECE - Mr. S.V.S Prasad - 9440840483 Department Head AERO - Dr.M.Satyanarayana Gupta - 9848339384 Department Head MECH - Dr.S.Madhu - 9160404635 Department Head MBA - Prof Dr M.V.Narasimha Rao - 9866589418 Department Head H&S - Dr. V. Radhika Devi - 9848472797

2. PLACEMENT & HIGHER STUDIES

MLR Institute of Technology has a unique distinction of placing their First Batch of B.Tech Students in their prefinal year of Study and MBA Students in Multi National Companies. The Institute has so far interacted with more than 69 Companies and 233 Selections from B.Tech/MCA and MBA Programmes have taken Place.

In this direction Apart from the Placements the Institute has arranged Summer Internship Programmes with Companies like Computer Amociates, Mind Tree M/s Infotech Enterprises Ltd, Mahindra Finance, Max New York Life Insurance, Nokia Ltd , Mahindra Finance, Bajaj Capital Ltd, Reliance Money and Tata AIG for Engineering and MBA Students to develop Mentor Relationships and to get to know about the Work Culture and gain Competencies to make them Industry Ready during their Study period.

The Institute has arranged Campus Recruitment drives Infosy, Mind Tree Ltd, Oracle, ADP, Mahindra Satyam, Infotech Enterprises Ltd, Keane India Ltd (NTT), IBM Technologies Pvt Ltd, Tata Advanced Systems, IBM, Syntel Inc, Tech-Synergy Pvt Ltd, Adithya Software Solutions, HDFC Bank Ltd, Medha Servo drives. NR Radio & Switches Pvt.Ltd. OsiTechnologies Ltd, Genpact, Reliance Money, Nagarjuna Caments Ltd & Oasis Software Informatics, Shoppers Shop, Trident Micro Systems India, SnapDeal.com, India Mart Ltd, Power Tech, Suchir India, Quartz Infra and Engineering Pvt Ltd, Gobrah Technologies Pvt Ltd, Elbit Diagnostics, Eprism Solutions, Geo Meme Strategic Consulting, India Info Line, Water Shed project of Govt of AP, Ocean Ship Maritime etc.

The CSE students visited Infosys Infosys for the SPARK Programme which is an orientation programme on Information Technology Space.

2.1 Industry Grade Skills required for Employment Behavioral and Communication Skills are recognized as important elements in professional development of an Engineer including English for specific purposes. Employers give considerable value to these diverse set of skills at the time of interviews.

In addition to course curriculum, every student will gain the following skills during the study period:  Analytical and Problem solving skills  Subject – specific knowledge  Research and improved decision making abilities  Oral communication skills  Managerial skills  Understanding of other cultures  Confidence and competence to work in International environment

As students are the future leaders, the Responsibility, Accountability and exhibiting the leadership skills should start from the first year of engineering. Every student is advised to read / practice from the following books;  Verbal and Nonverbal by RS Agarwal  Baron GRE  Wren and Martin English Grammer Book

2.2 Important criteria of Employment In addition to the industry grade skills required for employment, the most important criteria for employment is that the student should get a minimum of 60% in academics with no backlogs to make them eligible for campus recruitments. In the recent past, many companies stipulated a cut

of 68% for attending the interview / writing the test. Every student should Endeavour to achieve a minimum of 68% with no backlogs to make them suitable for picking up by good companies. Job Portals: 1. www.freshersworld.com 2. www.monster.com 3. www.naukri.com

2.3 Higher Studies M.Tech The Graduate Aptitude Test in Engineering (GATE) is an all-India examination administered and conducted in eight zones across the country by the GATE Committee comprising faculty from Indian Institute of Science, Bangalore and seven Indian Institutes of Technology on behalf of the National Coordinating Board - GATE, Department of Education, Ministry of Human Resources Development (MHRD), and Government of India.

Objective To identify meritorious and motivated candidates for admission to Post Graduate Programmes in Engineering, Technology, Architecture and Pharmacy at the National level. To serve as benchmark for normalization of the Undergraduate Engineering Education in the country.

This provides an opportunity for advanced engineering education in India. An M.E or M.Tech degree is a desirable qualification for our young engineers seeking a rewarding professional career. Engineering students, while in the final year of their degree course, spend considerable time in seeking an opening for studies in foreign universities. The students are advised to pursue M.Tech in IIT’s/NIT’s/University Colleges.

MBA Earning a Master’s of Business Administration (MBA) degree can provide you with management skills and business expertise that open new career opportunities to you. An MBA program will also launch you into the much higher pay range that upper level managers and executives enjoy. Furthermore, in the high-level positions, an MBA degree will allow you to hold and your work will often be more interesting and rewarding. The students are advised to pursue M.BA in IIM’s/XLRI/Reputed Business Schools.

Higher Studies Abroad TOEFL is mandatory for seeking admission in any academic course at any level- undergraduate, graduate or post graduate, in USA and Canada. Similarly UK Universities ask for IELTS for seeking admission to graduate and past graduate courses.

GRE The Graduate Record Examination (GRE) is administered by the Educational Testing Services (ETS) for admission into all graduate academic programs (except management) in universities across USA and Canada and some selected universities across the world including India. The exam is a Computer Adaptive Test and is administered at any of the Sylvan testing centers in the country after prior registration.

The GMAT is a Computer Adaptive Test administered online by Educational Testing Services (ETS) through Sylvan testing centers located in all the major cities in India. Those who wish to enroll for courses in Business Management in American universities have to take the GMAT test and submit their scores to the department.

2.4 Various Scholarships Available In India Bharat Petroleum Scholarship For Higher Studies | Balarama Digest Scholarship | Central Institute of Indian Languages | Fair & Lovely Foundation - Project Saraswati Scholarships | Government Of India Office of the Director General of Civil Aviation Scholarship | Homi Bhabha Centre For Science Education Tata Institute of Fundamental Research Research Scholarships | HSBC Scholarships | Indian Council Of Agricultural Research Award Of National Talent Scholarship In Agriculture | Indian Institute Of Geomagnetism Research Scholars | Invention Awards For School Children | Indian Oil Corporation Ltd (IOCL) - Scholarships | Jawaharlal Nehru Memorial Fund Jawaharlal Nehru Scholarships For Doctoral Studies | Junior Research Scholarships For Cancer Biology Tata Memorial Centre & Tata Memorial Hospital | Jaigopal Garodia Vivekananda Trust Scholarships | Lalit Kala Akademi - Scholarship | Mahindra All India Talent Scholarships For Diploma courses In Polytechnics | National Brain Research Centre Scholarships | NTPC Scholarships | National Institute Of Science Communication And Information Resources(NISCAIR) | National Board For Higher Mathematics(NBHM) | National Thermal Power Corporation Ltd.Scholarships | National Olympiad Programme | National Level Science Talent Search Examination - 2005 | Narotam Sekhsaria Scholarship Programme | National Brain Research Centre Scholarships, Post Doctoral Fellowships | National Aptitude Test | NIIT National IT Aptitude Test | Oil And Natural Gas Corporation Ltd (ONGC) Scholarships To SC/ST Students | Office Of The Director General of Civil Aviation Scholarships Stipend to the SC/ST Candidates | Rashtriya Sanskrit Sansthan - Scholarships | Scholarships To Young Artistes | Saf-Madanjeet Singh Scholarship | Sports Authority Of India - Sports Scholarships | SAF-Madanjeet Singh Scholarship | Spic Macay Scholarships | The Childrens Foundation - Scholarships | The L&T Build-India Scholarship | The Hindu-Hitachi Scholarships | The Paul Foundation Scholarships | Technology Information Forecsting and Assessment Council(TIFAC) Women Scientist Scholarship Scheme | The Young Talent IT Scholarship The Dr.GB Scholarships Foundation |

Website for Higher Studies: 1. www.higherstudyabroad.org 2. www.highereducationinindia.com

3. STUDENT CAREER ORIENTED PROFESSIONAL CERTIFICATION COURSES

As per the career plan for students of MLR Institute of Technology with a view to bridge the gap between Industry and Academia, it has been planned to equip every student with at least three International / National certification by the time he / she completes the course of study. The details of the certification courses are given below:

Branch Year Name of the Certification Course

2nd Year Certificate Information Technology IBM Certified DB2 Database Associate, 3rd Year Computer Science and Infosys Campus Connect Engineering / IT / MCA IBM Certified Rational Application 4th Year Developer 4th Year SUN Certified Java Programmer Institute of Electronics and 2nd Year Telecommunication Engineering Electronics and rd Communication Engineering 3 Year Motorola @ CAMPUS 4th Year IBM Certified DB2 Database Associate

2nd Year Certificate in AutoCAD

Aeronautical Engineering 3rd Year Certificate in HighPerMesh

4th Year Certificate in CATIA

2nd Year Certificate in AutoCAD

Mechanical Engineering 3rd Year Certificate in HighPerMesh

4th Year Certificate in CATIA

3.1 Help Desk The college has set up a Help Desk for Career Guidance and overseas education. The aim of the Help Desk is to provide a flatform for the students to choose the Right Destination. The students can reach the Help Desk in person or through mail at email id [email protected]

4. PERFORMANCE MONITORING AND GUIDANCE

4.1 Student Feedback In case the students find it difficult to cope up / understand a particular subject, they are advised to discuss it with a. The Concerned Teacher b. The Class Teacher c. The Department Head d. The Principal Students can use the suggestion boxes for communicating feedback. Students should mention their names so that they can be informed of the progress / more details / clarifications can be obtained.

4.2 Class Teacher Every class is assigned a Class Teacher (a faculty member). Students can directly discuss their college related or personal problems related to studies with them. The Class Teachers are accessible to the students and they can talk to the Class Teacher or whenever they are free from class / lab work. Class Teacher will meet with the class representative on daily basis to discuss their day-to-day difficulties if any.

4.3 Class Representatives and their roles Two students from each class are selected as the Class Representatives from the department basing on their academic performance and discipline. Department Head makes the selections.

Responsibilities of the Class Representatives:  Collection of MIS format from Class Teacher daily.  Communicating the departmental / college directives & information to the students.  Collecting the feedback of difficulties faced by the students and communicating Suggestions for improvements.  Coordinating academic events and co-curricular activities.  Encourage students to interact for better studies, sharing books and notes.  Compilation and submission of MIS form to class teacher at the end of the period.

4.4 Performance Counseling Mentors will evaluate the student individually for the following: a. Less marks in internal exams b. Continuous absence (3 days) and shortage of attendance c. Not understanding the subject d. Students from Telugu medium e. Assistance for back log subjects etc. f. Communication with parents g. Provide help to back log students

4.5 Remedial Classes / Tutorial / Revisions Remedial Classes are conducted for students who are weak and who do not perform well in their internal examinations / class tests or for the students who want extra help. Slots in the time table

have been reserved for Tutorial where in the students are helped to solve the question in the class itself.

4.6 Backlog Management The Mentors maintain a complete record of Examination results of each student and they counsel and guide them in preparing for backlogs. Students are provided with material and important questions are discussed.

4.7 Correspondence with parents Parents will be informed about the performance of their ward from time to time in the semester. However, parents are requested to be in touch with the Student mentor / Department Head on a regular basis. Further, parents are sent sms on daily bases if their wards do not attend the college.

5. RULES AND REGULATIONS FOR STUDENTS

5.1 Administrative: 1. Students, admitted into this College, are deemed to have agreed to the rules and regulations of the college, as laid down by the College Authorities from time to time, and the rules lay down in this leaflet, issued at the time of admission. 2. Students should inform any changes in the addresses/Phone No. of their parents / guardians to the college office. 3. The college shall communicate to the parents \ guardians of the students from time to time regarding the regularity and performance in the examinations of their wards. The case of serious indiscipline on the part of the students (s) may also be communicated to parent (s) \ guardian (s).

5.2. Academic: 1. Students should attend the classes in - time. Late- comers shall not be permitted to enter the class room and they are likely to loose the attendance. 2. Students are expected to be regular to the classes. The students Shall not absent themselves for classes without prior approval. Prior permission shall be taken from concerned counselor and submitted to the Head of the Department. 3. In case of ill-health, the student should submit the medical certificate along with prescription, etc., from a registered medical doctor. The student should get the medical certificate within two days from the date of reporting to the college after iII health and also produce a letter from Father/ Mother regarding ill-health. Permission on medical grounds shall not be granted for one or two days. 4. The students should come to the laboratories with the prescribed uniform. 5. If a student disturbs the class or makes mischief, he / she will be marked absent and may be expelled from the class. 6. Students shall spend their leisure time in the library/computer center. 7. Students are expected to put up the minimum aggregate percentage of attendance (75%) as laid down by the JNT University. Students, falling short of 75% of attendance shall not be promoted to the next Semester \ Class. 8. Parents \ guardians of the students can contact the college authorities either in person or by post regarding discipline, regularity in attending classes, performance in the examinations, etc., of their wards.

5.3 Dress Code: 1. Students are expected to attend the college properly dressed. They should wear the prescribed uniform while attending laboratory classes. 2. Students are expected to carry the identity cards, issued by the college, in the campus. They are required to show the identity cards at the library, computer center, office, etc. Students without Identity Cards are not allowed in to the laboratory classes.

5.4 Discipline & Punctuality: 1. No student shall enter or leave the class room without the permission of the teacher. 2. Calling students out of their class rooms while the lecture is in progress is prohibited. 3. Students are required to help in keeping the rooms, buildings, and premises clean and tidy. Writing or sticking up of posters and notices on the walls is strictly prohibited. 4. Smoking, Consumption of alcohol, intoxicating drinks or drugs is strictly prohibited in and around the college premises. Those indulging in such activities will be put severely or expelled. 5. Students are expected to behave well with the staff, other students and the general public. Any misbehavior, coming to the notice of the college authorities, will be severely dealt with.

6. The conduct of the students should be exemplary not only within the premises of the college but also outside. This will help in maintaining the image and status of the college.

7. Students are required to observe silence at all times in the college campus. They shall not talk in loud tone or call each other by shouting. 8. Students are prohibited from loitering in the verandahs / campus during class hours, and sitting on the steps, stair-cases or parapet walls. 9. Students are not permitted to resort to strikes and demonstrations within the campus. Participation in such activity entails their dismissal from the college. Any problem they face 11 may be represented to the Counselor / Head of the Department / Principal. 10. Students are prohibited carrying Cell Phones and organizing any meeting or entertainment in the college campus without the permission of the college authorities. 11. The entry of outsiders without permission is prohibited. Any student found responsible for bringing outsiders into the campus for settling personal disputes with other students, shall be expelled from the college. 12. The college is entitled to take any disciplinary action, which is deemed necessary in the case of any indiscipline on the part of the students. The same will be reflected on the Conduct Certificate issued at the time of leaving the college. 13. No Student Unions, except Professional Associations, are permitted in the college. 14. If the students cause any damage to the college property knowingly or unknowingly individually or in a group they have to pay 5 times to cost of property damaged them. All the students are collectively responsible for the proper maintenance college property i.e. building, furniture, lab equipment, garden, playgrounds, etc., recovery, calculated on semester to semester basis, will be collected along with examination fee for the semester. 15. Students should keep their vehicles only at the parking place allotted for the purpose. Vehicle riding in the campus is strictly prohibited. 16. Sitting on the parapet wall and Riding beyond the parking limits, the fine will be imposed to Rs.100.00 17. Breakage or loss of equipment /property as decided by the appropriate authority 18. The Principal/Director may, on the recommendation of the Head of the Department, or otherwise, inflict the following punishments in the interests of the student discipline and the Institution: fined, curtailment attendance, denial of promotion to next semester, suspension, expulsion or such other action as deemed necessary for the maintenance of discipline in the campus.

5.5. Lab Classes: All students must attend lab classes without fail. Those absent shall follow this procedure laid down in the prescribed format explaining valid reasons and obtain permission to attend the future classes.

5.6 Fee: 1. All students admitted into this college, will be required to pay the prescribed tuition fee and other specified fees. Failure of the same will result in the cancellation of admission. No portion of fees will be refunded under any circumstances. If any student wishes to change the college or discontinue the course at any point for any reason, he \ she shall not be permitted to do so unless he \ she pays balance amount of four years fees which he \ she would have to pay, if he \she continued till the completion of the course. His \ Her original certificates including I.e., etc., will be issued only after all the dues as stated above, are cleared by the students. All senior students must pay the college fee every year on or before the 15th of July irrespective of the reopening of the college. If they fail the fine will be imposed as per norms of the management. 2. Miscellaneous fee paid for expenditure related to training programs i.e., technical or soft skills

etc., is not refundable. 3. Other than the above, if any fees are levied by the University the student has to be pay the same.

5.7. Transport: All students who are availing the college bus facility must carry the bus-pass and must produce when demanded, failing which they will not allowed to travel in the bus. All students must travel in the allotted bus and routes. They should not change but occupy only their allotted seats throughout. Unauthorized students caught in the bus for not having the bus pass, should pay even if they traveled for one day also. First and second year are not allowed to bring two- wheelers.

5.8. Library Rules 1. Library Books will be issued for 15 days time and renewal depends upon the demand of the book. 2. Silence should be strictly maintained in the library. 3. Students are responsible for the library borrower card issued to them. Loss of the library card should be reported in writing to the circulation section immediately. Duplicate library borrower card will be issued on payment of Rs.150/- after a week time from the date of application for duplicate cards. 4. The Library borrower card is not transferable. 5. Library books must be returned on or before the due date. Any student failed to do so, 1st week –Rs.1/-per day/per book, 2nd week – Rs.2/-per day/per book and 3rd week – Rs.3/-per day/per book penalty will be imposed From 4th week-Rs.5/-per day/per book penalty will be imposed. 6. Students shall not make any sort of conversation in any part of the library, causing inconvenience to others. 7. Students shall not bring their belongings inside the library and should keep them outside the library. 8. Students leaving from the library should be checked at the exit. 9. Tearing of pages/stealing of books will invite suspension from using of the library facilities and further disciplinary action will be taken against such students, as per college norms. 10. The borrower shall replace the New book within 7 days, otherwise, he/she has to pay 3 times of the book cost, along with fine. In case of lose of book.

5.9. General: 1. All the students admitted in this college have to give an undertaking to abide by the rules and regulations of this college in prescribed format given by the college. 2. All the students should attend the college after vacations (Dasara / Sankranthi / Christmas / Semester term / summer) on the re-opening day without fail. 3. Students must deposit all the relevant original certificates and documents at the time of the admission Office and they will not be returned until completion of the course. 4. Admission of any student can be cancelled by the Management at any point during the course for reasons which are not in consonance with the rules and regulations and which are detrin the reputation of the college. 5. All the Students are here by informed that college authorities will not take any responsibility for loss or theft of your valuable items and money kept in your bags or some where else. Hence I request all the students are not to keep your valuables in class room or anywhere without your presence. 6. Fee For Issue Of Duplicates a) Duplicate Hall ticket Rs. 100.00 b) Duplicate Identity Card Rs. 100.00

c) Duplicate College Bus Pass Rs. 50.00 d) Duplicate Study Certificate for same purpose Rs. 50.00 e) Xerox copies of OD’s Rs. 50.00

All Breakage etc., penalties will be displayed on the Notice Board, and must be paid by the student and no student will be allowed to write examination or internal test or laboratory test, if penalties are not paid by the due date specified in the notice or circular.

5.10. Ragging Ragging in any form inside or outside the college campus is banned/Prohibited vide Ragging Act 26 of AP. legislative Assembly 1997. Those who indulge in this uncivilized activity are liable for severe disciplinary actions besides being liable for prosecution.

SALIENT FEATURES Ragging means doing an act which causes or is likely to cause insult 'or annoyance or fear or apprehension or threat or intimidation or outrage of modesty or injury to a student. S. Nature of Ragging Punishment No. Imprisonment Upto 6 Month 1 Teasing, Embarrassing and Humiliating or Fine Upto Rs 1000/- or Both. Assaulting or using criminal Force or criminal Imprisonment Upto 1 Year or Fine Upto 2 intimidation Rs 2000/- or Both. Wrongfully restraining or Confining or causing Imprisonment Upto 2 Years or Fine Upto 3 hurt Rs 5000/- or Both.

Causing grievous hurt kidnapping Or raping or Imprisonment Upto 5 Years or Fine Upto 4 committing unnatural offence Rs 10000/- or Both Imprisonment Upto 10 Years or fine 5 Causing death or abating Suicide Upto Rs. 50000/- or Both

Note: 1. A student convicted of any of the above offences, will be, dismissed from the college 2. A student imprisoned for more than six months for any of the above offences 'will not be admitted in any other College. 3. A student against whom there is prima facie evidence of ragging in any form will be suspended from the college immediately.

Prohibition of Ragging 1. Ragging is prohibited as per act 26 of AP. Legislative assembly, 1997. 2. Ragging entails heavy fines and/or imprisonment. 3. Ragging invokes suspension and dismissal from the college. 4. Outsiders are prohibited from entering the college premises without permission. 5. All students must carry their identity cards and show them when Demanded. 6. The principal and staff will visit and inspect the rooms at any time. 7. Suspended students are debarred from entering the campus except when required to attend enquiry and to submit an explanation .

6. ACADEMIC REGULATIONS MLR17 FOR AUTONOMOUS. (REGULAR) Applicable for the students of B.Tech. (Regular) from the Academic year 2018-19 and onwards

6.1. Award of B.Tech. Degree A Student will be declared eligible for the award of the B.Tech. Degree if he fulfills the following academic regulations: i) Pursued a course of study for not less than four academic years and not more than eight academic years. ii) Register for 224 credits and secure 216 credits. 6.2. Students, who fail to fulfill all the academic requirements for the award of the degree within eight academic years from the year of their admission, shall forfeit their seat in B.Tech Course.

6.3. Credits

I Year Semester Periods / Periods / Credits Credits Week Week 03+1/03 06 04 04 Theory 02 04 ------

Practical 03 04 03 02 03 02 Drawing 02T/03D 06 06 04 Mini Project ------02

Comprehensive Viva Voce ------02

Seminar ------6 02

Project ------15 10

6.4. Distribution and Weight age of Marks i. The performance of a student in each semester / I year shall be evaluated subject – wise with a maximum of 100 marks for theory and 75 marks for practical subject. In addition, Industry oriented mini-project, seminar and project work shall be evaluated for 50,50 and 200 marks respectively. ii. For theory subjects the distribution shall be 25 marks for Internal Evaluation and 75 marks for the End-Examination. iii. For theory subjects, during the semester there shall be 2 midterm examinations. Each mid term examination consists of objective paper for 10 marks and subjective paper for 15 marks with a duration of 1 hour 50 minutes (20 minutes for objective and 90 minutes for subjective paper). iv. For practical subjects there shall be a continuous evaluation during the semester for 25 sessional marks and 50 end examination marks. Out of the 25 marks for internal, day-to-day work in the laboratory shall be evaluated for 15 marks and internal examination for practical shall be evaluated for 10 marks conducted by the concerned laboratory teacher. The end examination shall be conducted with external examiner and laboratory teacher. The external examiner shall be appointed from the cluster of colleges as decided by the University examination branch.

v. For the subject having design and / or drawing, (such as Engineering Graphics, Engineering Drawing, Machine Drawing) and estimation, the distribution shall be 25 marks for internal evaluation (15 marks for day-to-day work and 10 marks for internal tests) and 75 marks for end examination. There shall be two internal tests in a Semester and the better of the two shall be considered for the award of marks for internal tests. However in the I year class, there shall be three tests and the average of best two will be taken into consideration. vi. There shall be an industry-oriented mini-project, in collaboration with an industry of their specialization, to be taken up during the vacation after III year II semester examination. However, the mini project and its report shall be evaluated with the project shall be submitted in report form and should be presented before the committee, which shall be evaluated for 50 marks. The committee consists of an external examiner, head of the department, the supervisor of mini project and a senior faculty member of the department. There shall be no internal marks for industry oriented mini project. vii. There shall be a seminar presentation in IV year II semester. For the seminar, the student shall collect the information on a specialized topic and prepare a technical report, showing his understanding over the topic, and submit to the department, which shall be evaluated by the Departmental committee consisting of Head of the department, seminar supervisor and a senior faculty member. The seminar report shall be evaluated for 50 marks. There shall be no external examination for seminar. viii. There shall be a comprehensive Viva-Voce in IV year II semester. The Comprehensive Viva-Voce will be conducted by a Committee consisting of (i) Head of the Department (ii) two Senior Faculty members of the Department. The comprehensive Viva-Voce is aimed to assess the students’ understanding in various subjects he/she studied during the B.Tech course of study. The comprehensive Viva-Voce is evaluated for 100 marks by the Committee. There are no internal marks for the comprehensive viva-voce. ix. Out of a total of 200 marks for the project work, 50 marks shall be for Internal Evaluation and 150 marks for the End Semester Examination. The End semester Examination (viva-voce) shall be conducted by the same committee appointed for industry oriented mini project. In addition the project supervisor shall also be included in the committee. The topics for industry oriented mini project, seminar and project work shall be conducted at the end of the IV year. The Internal Evaluation shall be on the basis of two seminars given by each student on the topic of his project. x. Laboratory marks and the sessional marks awarded by the college are not final. They are subject to scrutiny and scaling by the University wherever necessary. In such cases, the sessional and laboratory marks awarded by the College will be referred to a Committee. The Committee will arrive at a scaling factor and the marks will be scaled as per the scaling factor. The recommendations of the Committee are final and binding. The laboratory records and internal test papers shall be preserved in the respective institutions as per the University norms and shall be produced to the Committees of the University as and when the same is asked for.

6.5. Attendance Requirements: i. A student shall be eligible to appear for University examinations if he acquires a minimum of 75% of attendance in aggregate of all the subjects. ii. Shortage of Attendance below 65% in aggregate shall in NO case be condoned. iii. Condonation of shortage of attendance in aggregate up to 10% (65% and above and below 75%) in each semester or I year may be granted by the College Academic Committee. iv. A student will not be promoted to the next semester unless he satisfies the attendance requirement of the present semester / I year, as applicable. They may seek re-admission for that semester / I year when offered next.

v. Students whose shortage of attendance is not condoned in any semester / I year are not eligible to take their end examination of that class and their registration shall stand cancelled. vi. A stipulated fee shall be payable towards condonation of shortage of attendance.

6.6. Minimum Academic Requirements: The following academic requirements have to be satisfied in addition to the attendance requirements mentioned in item no.6 i. A student shall be deemed to have satisfied the minimum academic requirements and earned the credits allotted to each theory or practical design or drawing subject or project if he secures not less than 35% of marks in the end examination and a minimum of 40% of marks in the sum total of the internal evaluation and end examination taken together. ii. A student shall be promoted from II to III year only if he fulfills the academic requirement of 37 credits from one regular and one supplementary examinations of I year, and one regular examination of II year I semester irrespective of whether the candidate takes the examination or not. iii. A student shall be promoted from third year to fourth year only if he fulfills the academic requirements of total 62 credits from the following examinations, whether the candidate takes the examinations or not. a) Two regular and two supplementary examinations of I year. b) Two regular and one supplementary examinations of I semester. c) One regular and one supplementary examinations of II year II semester. d) One regular examination of III year I Semester. iv. A student shall register and put up minimum attendance in all 200 credits and earn the 200 credits. Marks obtained in all 200 credits shall be considered for the calculation of percentage of marks. v. Students who fail to earn 200 credits as indicated in the course structure within eight academic years from the year of their admission shall forfeit their seat in B.Tech course and their admission shall stand cancelled. Department of CSE

7. Course Calendar for the Year (Autonomous)

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8. IV YEAR CSE COURSE STRUCTURE (MLR 15)

CODE SUBJECT L T/P/D C

CRYPTOGRAPHY & NETWORK SECURITY A10539 1 3 3

A10540 CLOUD COMPUTING 1 3 3

A10541 DATA MINING & WAREHOUSING 3 1 3

A10547 BIG DATA ANALYTICS 3 1 3

A2IT17 3 1 SOFTWARE TESTING FUNDAMENTALS 3

A10549 CRYPTOGRAPHY & NETWORK SECURITY LAB - - 3

A10550 CLOUD COMPUTING LAB - - 3

A10551 DATA MINING & WAREHOUSING LAB - - 3

Note: All End Examinations (Theory and Practical) are of three hours duration. P- Practi T – Tutorial L-Theory cal C – Credits

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9. CRYPTOGRAPHY AND NETWORK SECURITY

9.0 COURSE DESCRIPTION

Course Title CRYPTOGRAPHY AND NETWORK SECURITY Course Code A10539 Regulation R15-MLRIT Lectures Tutorials Practical’s Credits Course Structure 3 1 - 3 Course Coordinator Sk.Khaja Shareef Team of Instructors Dr. N Chandra Shekar Reddy , Mrs K Archana, Mrs T Nirmala

9.1COURSE OVERVIEW:

This course will emphasize on principles and practice of cryptography and network security: classical systems, symmetric block ciphers (DES, AES, other contemporary symmetric ciphers), linear and differential cryptanalysis, perfect secrecy, public-key cryptography algorithms for factoring and discrete logarithms, cryptographic protocols, hash functions, authentication, key management, key exchange, signature schemes, email and web security, viruses, firewalls, digital right management, and other topics. In this course students will learn as aspects of network security and cryptography.

9.2 PREREQUISITE(S):

Level Credits Periods / Week Prerequisites

UG 3 5 Basic Mathematics and Computation skills.

9.3 COURSE ASSESSMENT METHODS:

a) Marks Distributions (Traditional Evaluation methods)

University Total Session Marks (25M) End Marks Exam Marks Mid Semester Test There shall be two midterm examinations. Each midterm examination consists of subjective type and objective type tests. The subjective test is for 10 marks of 60 minutes duration. 75 100 Subjective test of shall contain 4 questions; the student has to answer 2 questions, each carrying 5 marks The objective type test is for 10 marks of 20 minutes duration. It consists of 10 Multiple choice and 10 objective type questions, the student has to answer all the MLR Institute of Technology, Dundigal, Hyd-500043 Page 3

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questions and each carries half mark. First midterm examination shall be conducted for the first two and half units of syllabus and second midterm examination shall be conducted for the remaining portion. b) Expected Learning Outcomes and Methods for Assessing S. Expected Learning Outcomes Assessment method (s) No Ability to Identify basic security attacks A Quiz on security attacks and services. and services Case studies on symmetric and Ability to learn symmetric and asymmetric B asymmetric key algorithms for key algorithms for cryptography cryptography Case studies on Key Management Construct Key Management techniques C techniques and importance of number and importance of number Theory Theory Group Activity/ solve various To solve Authentication functions the Authentication functions the manner in D manner in which Message Authentication which Message Authentication Codes Codes and Hash Functions works and Hash Functions works. Ability to examine the issues and structure Case study group wise activity / model of Authentication Service and Electronic design on examine the issues and E Mail Security structure of Authentication Service and Electronic Mail Security

9.4. EVALUATION SCHEME: S. No Component Duration Marks 1 I mid 80 M 20 2 I assignment - 05 3 II mid 80 M 20 4 II assignment - 05 5 External examination 3 Hours 75

9.5 COURSE OBJECTIVES AND COURSE OUTCOMES

Course Outcomes Course Objectives Blooms Level At the end of the course I. To provide deeper understanding into cryptography, its application a. Students able to Identify basic to network security, BL 1 & 2 security attacks and services threats/vulnerabilities to networks and countermeasures. II. To explain various b. Students able to Use symmetric approaches to Encryption and asymmetric key algorithms for techniques, strengths of Traffic BL 3,4 Confidentiality, Message cryptography and Design a security Authentication Codes. solution for a given application

c. Students able to develop Analyze

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Key Management techniques and importance of number Theory. III. To familiarize Digital Signature d. Students able to develop Standard and provide solutions Authentication functions the manner BL 3,4 & 5 for their issues. in which Message Authentication Codes and Hash Functions works. IV. To familiarize with e. Students will be able to examine cryptographic techniques for secure (confidential) the issues and structure of communication of two parties BL 4,5 & 6 Authentication Service and Electronic over an insecure (public) channel; verification of the authenticity of Mail Security the source of a message. BLOOMS LEVEL (BL) BL 1: Remember / knowledge BL2: Understanding BL3: Apply BL 4: Analyze BL 5: Evaluate BL 6: Create

9.6 HOW COURSE OUTCOMES ARE ASSESSED:

Proficiency Bloom’s Program Outcomes Level assessed by Level An ability to apply the knowledge of mathematics, Computing, Science and engineering to solve Computer Lectures and Apply A H Problem Science and Engineering problems. Solving (Fundamental engineering analysis skills). An ability to design and conduct engineering experiments, Design Exercises Apply B as well as to analyze and interpret data. (Information S and Retrieval skills). Assignments An ability to design and construct a hardware and Assignments, Apply and C software system, component, or process to meet desired H Lectures and Analyze needs, within realistic constraints. (Creative skills). Exams Graduates will demonstrate an ability to visualize and work on laboratory and Multi-disciplinary tasks Mini and Apply D S Micro individually or as a member within the teams. (Team Projects work) An ability to demonstrate skills to use the techniques, modern engineering Tools, Software and equipments Lectures and Apply E S Problem necessary to analyze computer engineering Solving Problems.(Engg. Problem solving Skills) An understanding of professional, social and ethical F N ------responsibility ------An ability to recognize the global issues like green initiatives and alternate energy sources and to take G S Assignments Analyze technology to villages and to recognize the rural and Justify requirements. (Engg. Application Skills)

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The broad education necessary to understand the impact Assignments Analyze H of engineering solutions in a global, economic, S environmental, and societal context. Graduate will develop confidence for self education and acquire new knowledge in the computing discipline and Class Test & Analyze I S ability and practice for Multidisciplinary tasks as a Seminars member within the teams

Understan J To communicate effectively S Seminars d & Analyze Class Tests An ability to use the techniques, skills and modern & Group Apply K S engineering tools necessary for Engineering practice. Activity in class room Graduates are able to participate and succeed in competitive ------L N ------examination like GRE, GATE, TOEFL, GMAT etc.(Continuing Education ) The use of current application software and the design and Text Book use of operating systems and the analysis, design, testing Problems as Apply M S and documentation of computer programs for the use in part of Computer Science and engineering technologies. Assignment Design and N An ability to setup an enterprise.(Employment Skills) S Placement Develop

N= None S= Supportive H = Highly Related

9.7 SYLLABUS

UNIT – I INTRODUCTION: Security trends, The OSI Security Architecture, Security Attacks, Security Services and Security Mechanisms, A model for Network security. CLASSICAL ENCRYPTION TECHNIQUES: Symmetric Cipher Modes, Substitute Techniques, Transposition Techniques, Rotor Machines, Stenography.

UNIT - II BLOCK CIPHER AND DATA ENCRYPTION STANDARDS: Block Cipher Principles, Data Encryption Standards, the Strength of DES, Differential and Linear Crypt Analysis, Block Cipher Design Principles. ADVANCED ENCRYPTION STANDARDS: Evaluation Criteria for AES, the AES Cipher. MORE ON SYMMETRIC CIPHERS: Multiple Encryption, Triple DES, Block Cipher Modes of Operation, Stream Cipher and RC4. INTRODUCTION TO NUMBER THEORY: Prime Numbers, Fermat‘s and Euler‘s Theorem, Testing for Primality, The Chinese Remainder Theorem, Discrete logarithms.

UNIT - III PUBLIC KEY CRYPTOGRAPHY AND RSA: Principles Public key crypto Systems, Diffie Hellman Key Exchange, the RSA algorithm, Key Management, , Elliptic Curve Arithmetic,

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Elliptic Curve Cryptography. MESSAGE AUTHENTICATION AND HASH FUNCTIONS: Authentication Requirement, Authentication Function, Message Authentication Code, Hash Function, Security of Hash Function and MACs. HASH AND MAC ALGORITHM: Secure Hash Algorithm, Whirlpool, HMAC, CMAC. DIGITAL SIGNATURE: Digital Signature, Authentication Protocol, Digital Signature Standard.

UNIT - IV AUTHENTICATION APPLICATION: Kerberos, X.509 Authentication Service, Public Key Infrastructure. EMAIL SECURITY: Pretty Good Privacy (PGP) and S/MIME. IP SECURITY: Overview, IP Security Architecture, Authentication Header, Encapsulating Security Payload, Combining Security Associations and Key Management.

UNIT - V WEB SECURITY: Requirements, Secure Socket Layer (SSL) and Transport Layer Security (TLS), Secure Electronic Transaction (SET), Intruders, Viruses and related threats. FIREWALL: Firewall Design principles, Trusted Systems.

TEXT BOOKS: 1. William Stallings (2006), Cryptography and Network Security: Principles and Practice, 4th edition, Pearson Education, India. 2. William Stallings (2000), Network Security Essentials (Applications and Standards), Pearson Education, India. REFERENCE BOOKS: 1. Charlie Kaufman (2002), Network Security: Private Communication in a Public World, 2nd edition, Prentice Hall of India, New Delhi. 2. Atul Kahate (2008), Cryptography and Network Security, 2 nd edition, Tata Mc Grawhill, India. 3. Robert Bragg, Mark Rhodes (2004), Network Security: The complete reference, Tata Mc Grawhill, India.art, Cengage Learning, India Edition

9.8 COURSE PLAN: Course Blooms Levels Lecture Learning Topic Reference No. Outcomes Explain the objectives and Understanding / L1 functionality of Security Comprehension T1:1.1-1.5 A trends, Describe about the OSI Creating / Synthesis Security Architecture how T1:1.9-1.10 L2 cryptography and network T2: 1.2 A security have evolved Explain the Security Understanding / T1:1.4, 1.6- Attacks , Security Services Comprehension 1.8, 2.1- L3 of cryptography and 2.3 A,B network security. L4 Explain the concepts of Understanding / T1 :2.5,2.6 L5 A Security Mechanisms Comprehension R1: 1.6 Explain the importance of A Understanding / L6 T2:2.5 A model for Network security. Comprehension L7 A Explain the Symmetric Understanding / T1:3.1

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Cipher Modes. Comprehension T2: 3.1-3.2 Understanding / T1:3.1, Explain the Substitute Comprehension 4.1-4.5 L8 Techniques T2: 3.3, T2: B 4 Understanding / T1:5.1-5.2 Describe Transposition L9 Comprehension T2: 9 Techniques. B R1- 2.4 Creating / Synthesis T1:5.3 Compare the performance L10 L T2- 9.2 of the Rotor Machines B,C R1- 2.4 Understanding / T1:5.4 Explain about the Comprehension T2: 10.3- L11 L Stenography 10.6 A,D R1- 2.4 Creating / Synthesis T1:5.4 Discuss Block Cipher L12 L R1- 2.4.4 Principles. A,D T2:10.2 Discuss the importance of Creating / Synthesis T1:5.5 L13 L D Data Encryption Standards R1- 2.4.6 Explain the Creating / Synthesis T1:6.1-6.2 L14 L A,D,E Strength of DES R1: 2.3 Describe reasons for using Creating / Synthesis T1:6.3-6.4 L15 L Differential and Linear R1:2.3 A,B Crypt Analysis Explain the importance of Understanding / T1:6.5-6.7 L16 Block Cipher Design Comprehension R1: 2.3 A,B Principles Explain about Evaluation Understanding / T1:8.1 -8.3 L17 A,B Criteria for AES Comprehension R1: 3 Understanding / T1:8.4-8.6 L18 Explain the AES Cipher. A,B,C Comprehension R1: 3.3 Summarize the Multiple Understanding / T1:9.1- L19 B,D Encryption Comprehension 9.2R1:3.3 Creating / Synthesis T1:9.4 L20 Describe Triple DES A,C R1: 3.4 Explain Block Cipher Understanding / L21 T1: 9.5-9.6 A,E Modes of Operation. Comprehension Summarize the Stream Understanding / T1:10.1-10.3 L22 C,D Cipher and RC4. Comprehension R1: 4.1- 4.2 Explain about Prime Understanding / T1:10.4-10.6 L23 C,D Numbers. Comprehension R1: 4.1- 4.2 Describe a Fermat‘s and Creating / Synthesis T1:11.1-11.2 L24 A,D,E Euler‘s Theorem R1: 4.3 Describe Testing for Creating / Synthesis T1: 11.3- L25 A,E Primality. 11.4 Summarize The Chinese Understanding / T1:11.5-11.6 L26 B,C Remainder Theorem Comprehension R1: 4.4 L27 A,D,E Analyze the various Understanding / T1: 12.1

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Discrete logarithms Comprehension T1:12.2-12.3 Discuss about the Principles Creating / Synthesis L28 A,E Public key crypto Systems Describe Diffie Hellman Creating / Synthesis T1:12.4 L29 A,D Key Exchange R1: 5.4 Creating / Synthesis T1:12.5-12.6 L30 Discuss the RSA algorithm. A,D R1:5.4 Understanding / T1:7.1-7.3 L31 Explain Key Management A,E Comprehension R1: 6.2 Understand Elliptic Curve Understanding / T1: 7.4 L32 A,E Arithmetic Comprehension R1: 6.6 Understand Elliptic Curve Understanding / T1:7.5 L33 A,E Cryptography Comprehension R1: 6.5 Understand Authentication Understanding / T1:7.6-7.7 L34 E Requirement Comprehension R1: 6.4 Compare and contrast Understanding / L35 T1:14.1 E Authentication Function Comprehension Describe the Message Creating / Synthesis L36 T1:14.4-14.7 B,C,E Authentication Code Describe Hash Function, Creating / Synthesis L37 Security of Hash Function T1:14.8-14.9 A,E and MACs Explain the objectives of Understanding / T1:11.5-11.6 L38 A,B,C Secure Hash Algorithm Comprehension R1: 4.4 Describe about the Understanding / T1: 12.1 L39 B,D Whirlpool, HMAC. Comprehension T1:12.2-12.3 Understanding / L40 Explain the CMAC A,C Comprehension Explain the concepts of Creating / Synthesis T1:12.4 L41 A,E Kerberos R1: 5.4 Explain the X.509 Understanding / T1:12.5-12.6 L42 C,D Authentication Service Comprehension R1:5.4 Explain the Public Key Understanding / T1:7.1-7.3 L43 C,D Infrastructure Comprehension R1: 6.2 Explain the Pretty Good Understanding / T1: 7.4 L44 A,D,E Privacy (PGP). Comprehension R1: 6.6 Creating / Synthesis T1:7.5 L45 Describe S/MIME A,E R1: 6.5 Compare the Overview, IP Creating / Synthesis T1:7.6-7.7 L46 B,C Security Architecture R1: 6.4 Explain about the Understanding / L47 T1:14.1 A,D,E Authentication Header Comprehension Discuss Encapsulating Understanding / L48 T1:14.4-14.7 A,E Security Payload Comprehension Discuss the importance of Creating / Synthesis L49 Combining Security T1:14.8-14.9 A,D Associations Explain the Understanding / T1:11.5-11.6 L50 A,D Key Management Comprehension R1: 4.4

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Describe reasons for Secure Understanding / T1: 12.1 L51 A,E Socket Layer (SSL) Comprehension T1:12.2-12.3 Explain the importance of Understanding / T1: 12.1 L52 Transport Layer Security Comprehension T1:12.2-12.3 A,E (TLS) Explain about Secure Creating / Synthesis T1:12.4 L53 Electronic Transaction R1: 5.4 A,E (SET) Explain the Intruders, Understanding / T1:11.5-11.6 L54 E Viruses related threats Comprehension R1: 4.4 Summarize the Firewall Understanding / T1: 12.1 L55 A,B,C Design principles Comprehension T1:12.2-12.3 Understanding / T1: 12.1 L56 Explain Trusted Systems. A,C Comprehension T1:12.2-12.3

9.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF COURSE OUTCOMES:

Course Outcomes Course Objective A B C D E I S S II S H H III H IV S H S

S=Supportive H=Highly Related

9.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: Course Program Outcomes Educational A B C D E F G H I J K L M N Outcomes a. S S S H b. H H S H H H c. S H H H H d. S S H S S S e. S H S

S=Supportive H=Highly Related

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9.11 OBJECTIVE QUESTIONS: UNIT-I

1. Passive attack is A. Replay B. masquerade C. traffic analysis D. none of these Answer: C 2. is responsible for technical management of IETF activities and internet standard process.

A. IESG B. IETF C. IAB D. rfc publication Answer: B

3. Fabrication is attack on A. Confidentiality B. Non-repudiation C. Authentication D. Availability Answer: C 4. In phase system is continuously improved bugs are eradicated and features that that did not make an earlier release are added. A. inception B. elaboration C. construction D. transition Answer: D

5. Man in middle attacks leads to A. HTTP session hijack A. FTP session hijack B. TCP session hijack C. UDP session hijack Answer: D

6. Security service , requires that neither the sender nor the receiver of a message be able to deny the transmission.

A. NonRepudiation B. Availability C. Authentication D. Confidentiality Answer: C

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7. Security service , requires that neither the sender nor the receiver of a message be able to deny the transmission. A. NonRepudiation B. Availability C. Authentication D. Confidentiality Answer: A

8. Hijacking HTTP session involves obtaining A. The URL B. Session ID C. IP address D. Mac Address Answer: B

9. How many types cipher block modes of operations A. 4 B. 5 C. 6 D. 3 Answer: D

10. The key length of 3DES algorithm is A. 56 B. 168 C. variable D. 128 Answer: B

11. In DES algorithm the mathematical function used is A. Addition B. Subtraction C. Inclusive OR D. Exclusive OR Answer: B

12. The number of rounds in AES is A. 16 B. 10 C. 15 D. 9 Answer: B

13. Message Authentication Code is calculated as a function of A. Key B. Message C. Arbitrary number D. Message, key Answer: D

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14. treats digrams in the plaintext as single units and translates these units into cipher text digrams A. Substitution Cipher B. Playfair cipher C. Monoalphabetic cipher D. Hill Cipher Answer: B

15. For a given message, it is feasible to find y # x such that H(x) = H(y) is called as A. Two – way encryption B. Strong collision C. One – way encryption D. Weak collision

Answer: D

16. Hijacking HTTP session involves obtaining A. The URL B. Session ID C. IP address D. Mac Address Answer: B

17. Interruption attacks are also called attacks A. Masquerade B. Alteration C. Denial of service D. Replay attacks Answer: A

18. DOS attacks are cause by A. Authentication B.Alteration C.Fabrication D. Replay attacks Answer: D

19. replicates itself by creating its own copies, in order to bring the network to a halt. A. Virus B. Worm C. Trojan horse D. Bomb Answer: A

20. Virus is a Computer A. File B. Program C. Database D. Network Answer: B MLR Institute of Technology, Dundigal, Hyd-500043 Page 13

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UNIT-II

1. scrambled message produce as output.

A. plain text B. secret key C. cipher text D. encryption Answer: A

2. is the process of attempting to discover the plain text or key.

A. cryptography B. cryptanalysis C. cipher text D. stream cipher Answer: B

3. The most widely used public-key algorithms are types.

A) 1 B) 2 C) 3 D) 4 Answer: B

4. Same key is used for encryption and decryption

A) Symmetric/Conventional encryption B) Public-key cryptography C) Both D) None Answer: A

5. RSA is

A) Rivest, Shyam, Adleman B) Ricest, Shamir, Alice C) Rivest, Shamir, Adleman D) None Answer: A

6. RSA Algorithm cipher text is

A) C=M^e(mod n) B) C=E^M(mode n) C) Both D) None Answer: A

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7. Key exchange is big problem

A) Encryption B) Decryption C) Conventional encryption D) Public-key cryptography Answer: C

8. Diffie-Hellman key algorithm public keys Ya=?

A. Ya=Xa mod q B. Yb=Xb mod q C. both D. None Answer: A

9. Diffie –Hellman key exchange algorithm cab be used only for A. Encryption B. Decryption C. Key management D. None Answer: C 10 Diffie-Hallman algorithm public key Yb=?

A. Ya=Xa mod q B. Yb=Xb mod q C. both D. None Answer: B

11 Diffie-Hallman algorithm secret key K by user A=?

A. K=Xa mod q B. K=Xa mod q C. K=(Yb)^ Xa mod q D. All Answer: A

12 Diffie- Hallman algorithm secret key K by user B=?

A. K=(Ya)^ Xb mod q B. K=Xb mod q C. Both D. None Answer: B

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13 DSS is

A. Digital System Standard B. Digital Signature Standard C. Digital Signature System D. All the above Answer: B

14 Kerberos is a protocol

A. Confidentiality B. Integrity C. Authentication D. All Answer: A

15 TGS is

A. Ticket Granting Service B. Ticket Granting Server C. Both D. None Answer: A 16 The general schemes for digital signatures are

A. Direct B. Arbitrated C. Both D. None Answer: C

17 Major issues of key management are

A. Key life time B. Key size C. Key exposure D. Both a,c Answer: D

18 Management and handling of the pieces of Secret information is generally referred to as

A. Key management B. DSS C. Digital Certificate D. None Answer: A

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19 To establish identies , encrypt information and digitally sign document

A. CA B. DSS C. PKI D. None Answer: D

20 In Greek mythlogy Kerberos is

A. Authentication B. Security C. Dog D. Multithreaded dog Answer: D

UNIT – III

1. Which of the following documents provides the description of a packet authentication extension to IPv4 and IPv6

A. RFC 2401 B. RFC 2402 C. RFC 2406 D. RFC 2408 Answer: D 2. Which of the following documents provides the description of a packet encryption extension to IPv4 and IPv6 A. RFC 2401 B. RFC 2402 C. RFC 2406 D. RFC 2408 Answer: D

3. Which among the following Routing Protocols is used by IP Security

A. OSPF B. OPSF C. UDP D. TCP Answer: C

4. The attack in which intruders create packets with false IP addresses and exploit applications that use authentication based on IP address is called

A. Packet sniffing B. IP Spoofing C. Eaves dropping D. Modification Answer: D

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5. A process by which packets from one network are broken into smaller pieces to be transmitted on another network is know as

A. segmentation B. bifurcation C. fragmentation D. segregation Answer: C

6. Which of the following documents provides an overview of security architecture

A. RFC 2401 B. RFC 2402 C. RFC 2406 D. RFC 2408 Answer: D

7. Which of the following documents provides Specification of key management capabilities.

A. RFC 2401 B. RFC 2402 C. RFC 2406 D. RFC 2408 Answer: D

8. Which of the following algorithms are used by IPSec to provide per- packet authentication and data integrity A. HMAC MD5 B. 3DES C. AES D. Digital signature s, based on RSA and DSA Answer: D

9. Which among the following is carried in AH and ESP headers to e the receiving system to select the Security associations under whic received packet will be processed

A. Security Paramete rs index B. Security Protocol identifier C. IP destination address D. Network address Answer: A

10. Masquerade is an attack on

A. Data retrieval B. Authentication C. Nonrepudiation D. Data access Answer: D

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11. IPSec is provided at the layer

A. Below transport Layer B. Below network layer C. At the application layer D. At the physical Answer: D

12. Which among the following indicates whether the security association is an AH or ESP security association.

A. Security Parameters index B. Security Protocol identifier C. IP destination on address D. Network Address Answer: D

13. Which among the following mechanisms assures the receiver that the received packet was transmitted by authorized person

A. Confidentiality B. Nonrepudiation. C. Authentication D. key management Answer: C

14. Which among the following mechanisms assures the receiver that the messages are received as sent,with no duplication, insertion, modification, reordering or replays.

A. Confiden tiality B. Nonrepudiation C. Authenti cation D. Integrit y Answer: A

15. Which among the following mechanisms prevents either sender or receiver from denying a transmitted message

A. Confidentiality B. Nonrepudiation C. Authenti cation D. Integrity Answer: D

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16. For transport mode AH using IPv4, where is AH inserted

A. After original IPheader & before IP payload B. Before original IP header & before IP payload C. Before original IP header & After IP payload D. After original IP header & after IP payload Answer: A

17. In relation to SNMP which of the following is defined by the monitoring of network parameters to enable early indication of deterioration in operation to be detected, and corrective action to be taken

A. Fault management B. Performance management C. Layer management D. Network management Answer: D

18. In relation to SNMP which of the following is defined by the ongoing adjustment to host and device configurations in a network without taking element out of service

A. Fault management B. Performance management C. Layer management D. Network management Answer: D

19. Which is a string of numbers, with each number representing a level in a hierarchical tree

A. MIB B. Trap C. OID D. SMI Answer: A

20. In relation to SNMP which of the following is defined by any network element that may be written to or read from, by a network manager

A. Managed object B. Network Object C. Routed object D. Managed subject Answer: D

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UNIT – IV

1 IDS may be configured to report attack occurrences. You just received a notification that an attack occurred, but after checking, you find that it really wasn't an attack at all. What is the term for this type of alarm?

A. True positive B. False positive C. True negative D. False negative Answer: A

2 Which of the following apply to network-based IDS?

A. Provides reliable, real-time intrusion data B. Remains active and transparent on the network C. Uses many network or host resources D. Becomes active when identifying intrusions Answer: C

3 Which of the following intrusion detection systems functions in current or real time to monitor network traffic?

A. Network based B. Host based C. Gateway based D. Router based Answer: A

4 Which of the following describes how a network-based IDS acquires data?

A. Passive B. Active C. Very quiet D. Very noisy Answer: A

5 What does active detection refer to when using an intrusion detection system (IDS)? A. An IDS that is constantly running 24 hours a day B. An IDS that responds to the suspicious activity by logging off a user C. An IDS that simply detects the potential security breach D. An IDS that shuts down the Internet after a suspected attack Answer: B

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6 Which among the following is not a password selection strategy

A. User education B. Computer-generated passwords C. Stego password checking D. Proactive password checking Answer: C

7 In which among the following strategies a system periodically runs its own password cracker to find guessable passwords.

A. Proactive password checking B. Reactive password checking C. Active password checking D. Underactive password checking Answer: B

8 In which of the following schemes the system checks to see if a password selected by a user is allowable and, if not rejects it.

A. Proactive password checker B. Reactive password checker C. Active password checker D. Under active password checker Answer: A

9 Threshold detection comes under which of the following

A. Statistical anomaly detection system B. Rule-based detection system C. Time stamp method D. Detection specific password scheme Answer: B

10 Which of the following is most useful when detecting network intrusions?

A. Audit policies B. Audit trails C. Access control policies D. Audit practices Answer: B

11 SOCKS service is located on

A. TCP port 1080 B. TCP port 1088 C. TCP port 1081 D. TCP port 1082 Answer: A

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12 Version 5 of SOCKS is defined in

A. RFC 1892 B. RFC 1928 C. RFC 1298 D. RFC 1289 Answer: B

13 Which among the following is typically set up as a list of rules based on matches to fields in the IP or TCP header

A. Packet filters B. Application level gateways C. Circuit level gateways D. Session gateway Answer: C

14 Discarding all packets containing the route information that the packet should take as it crosses the internet router is which attack

A. Source routing attack B. IP address spoofing C. any fragment attack D. IP sniffing Answer: A

15 SOCKS server runs on which of the following platform based firewalls

A. UNIX B. Windows C. DOS D. JAVA Answer: A

16 Which among the following is not a firewall

A. Packet Filters B. Application level gateways C. Circuit level gateways D. Session gateway Answer: D

17 Which among the following are default policies of a packet filtering router

A. discard, forward B. discard, retrieve C. delete, forward D. delete, retrieve Answer: A

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18 Discarding packets with an inside source address if the packet arrived on an external interface is a counter measure to which of the following attacks

A. IP address spoofing B. Source routing attack C. Tiny fragment attack D. IP sniffing Answer: D

19 Which of the following is also called a proxy server

A. packet filter B. application level gateway C. circuit level gateways D. session gateway Answer: B

20 which among the following is a system identified by the firewall administration as a critical strong point in the networks security

A. Base host B. Bastion host C. Borland host D. Prime host Answer: DS UNIT - V. 1. One of the problems with using SET protocol is

A. The merchants risk is high as he accepts encrypted credit card B. The credit card company should check digital signature C. The bank has to keep a database of the public keys of all customers D. The bank has to keep a database of digital signatures of all customers Answer: B

2. The bank has to have the public keys of all customers in SET protocol as it has to

A. Check the digital signature of customers B. Communicate with merchants C. Communicate with merchants credit card Company D. Certify their keys Answer: C

3. Which among the following SET transactions indicates that a responder rejects a message because it fails format or content verification tests

A. batch administration

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B. certificate inquiry and status C. credit D. error message Answer: A

4. Which of the following SET transactions allows a merchant to communicate information to the payment gateway regarding merchant batches

A. batch registration B. batch administration C. batch processing D. batch authorization Answer: D

5. Which of the following SET transactions allows a merchant to correct a previously request credit

A. payment capture B. capture reversal C. credit reversal D. purchase request Answer: A

6. The Secure Electronic Transaction protocol is used for

A. credit card payment B.cheque payment C.electronic cash payments D. payment of small amounts for internet services Answer: A

7. In SET protocol a customer encrypts credit card number using

A. his private key B. bank's public key C. bank's private key D. merchant's public key Answer: B

8. In SET protocol a customer sends a purchase order A. encrypted with his public key B. in plain text form C. encrypted using Bank's D. public key using digital Signature system Answer: C

9. Which among the following SET transactions allows the merchant to request payment from the payment gateway

A. payment capture B.capture reversal C.credit reversal

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D. purchase request Answer: A

10. Which among the following SET transactions allows a merchant to correct a previously request credit

A. payment capture B. capture reversal C. credit reversal D. purchase request Answer: B

11. Alert that indicates an inappropriate message was received as defined in the SSL specification is

A. bad _record _mac B. unexpected _message C. illegal _ parameter D. unsupported message Answer: D

12. Select which reasons secure electronic transaction ( SET) is preferred to SSL

A. the vendor can verify the address of the purchaser B. the person making the payment is the legitimate card holder C. the purchaser may verify that the vendor is authorized to engage in payment card transaction D. guarantees delivery of goods or services Answer: B

13. Which among the SSL specific protocols that use SSL record protocol is the simplest

A. change cipher spec protocol B. TCP C. IP D. Handshake protocol Answer: D

14. Which of the following is not a SSL handshake protocol message type A. Server _hello B. Server _hello C. client _hello D. client _hello Answer: B

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15. SSL is implemented over which layer A. TCP B. IP C. HTTP D. FTP Answer: A

16. The handshake protocol, the change cipher spec protocol and the alert protocol are defined as part of which of the following protocols

A. HTTP B. IP C. TCP D. SSL Answer: D

17. SSL sessions are created by which of the following

A. Cipher spec protocol B. TCP C. IP D. Handshake protocol Answer: D

18. A session state from SSL specification is not defined by which of the following parameters

A. Server write MAC secret B. Session identifier C. Master secret D. Peer certificate Answer: B

19. connection state from SSL specification is not defined by which of the following parameters

A. Client write MAC secret B. Server write key C. Client write key D. Session identifier Answer: B

20. Which is not a SSL record protocol operation

A. Adding MAC B. Compression C. Encryption D. Expansion Answer: D

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9.12 ASSIGNMENT QUESTIONS PART A(SHORT ANSWER QUESTIONS) S.No Questions Blooms Course Taxonomy Outcome level UNIT-I 1. State the need for security Remember 1 2. Define Confidentiality Remember 1 3. Explain why are some attacks called as passive? Understand 3 4. State what is Plain Text and Cipher Text Understand 5 5. State what is encryption and decryption Understand 1 UNIT- II 1. Asses the reason to study Feistal Cipher create 6 2. State the problems with Symmetric key Encryption Remember 1 3. Differentiate between diffusion and confusion Analyze 4 4. State the purpose of using S-boxes in DES Remember 1 5. Differentiate between linear and Analyze 4 differential cryptanalysis UNIT- III 1 Compare the types of attacks are addressed by evaluate message authentication 5 2 Define is message authentication code Remember 1 3 Solve the problem Kerberos is designed to address analyze 3 4 List three approaches to secure user Remember 1 authentication in a distributed environment 5 Asses the purpose of x.509 standard create 6 UNIT- IV 1 State what is S/MIME? Remember 1 2 Discuss where do you apply PGP? Understand 1 3 Discribe some functions of PGP. Remember 1 4 List the S/MIME Functions. Remember 1 5 Explain the methods for protecting the password file. Understand 1 UNIT- V 1 List services provided by SSL or TLS Remember 1 2 Describe how master secret is created from Understand 1 premaster secret in SSL 3 Describe how key materials are created from Understand 1 master secret in TLS 4 Define the goal of each phase in the Handshake Remember 1 protocol 5 Describe the role of compression in the Understand 1 operation of a virus

ASSIGNMENT QUESTIONS PART B(LONG ANSWER QUESTIONS)

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S.No Questions Blooms Course Taxonomy Outcome level UNIT-I 1 Explain in detail different passive and active attacks. Remember 1 2 Explain simple substitution techniques with an Remember 1 example. 3 Use Caesar cipher with key =15 to encrypt the message Understand 3 “Hello”. 4 What is the difference between mono alphabetic and Understand 5 poly alphabetic cipher? 5 What is symmetric cipher model? What are Understand 1 transposition ciphers? UNIT- II 1 Distinguish between Stream Cipher and Block Cipher Analyze 4 2 Explain the main concept of DES evaluate 5 3 Discuss the possible attacks on RSA Digital signatures create 6 4 Discuss the advantages and disadvantages of symmetric and Asymmetric key cryptography create 6 5 Explain Diffi-Hellman Key Exchange evaluate 5 UNIT- III 1 Explain the three threats associated with user authentication over a network or Internet. Understand 5 2 Differentiate between a message authentication code Analyze and one way hash function 4 3 Explain in what ways can a hash value be secured evaluate so as to provide message authentication 1 4 Explain some approaches to produce message evaluate 1 authentication 5 Differentiate the principal differences between Analyze version4 and version5 of Kerberos. 4 UNIT- IV 1 Illustrate the functions provided by S/MIME. Analyze 4 2 Illustrate the five principal services provided by PGP? Analyze 4 3 Explain the different four techniques used to avoid evaluate guessable passwords? 1 4 Design the PGP Cryptographic function for create Authentication only. 6 5 Outline the Cryptographic algorithm used in S/MIME. Analyze 5 UNIT- V 1 List four kinds of security threats in the network. Understand 1 2 Explain any two design goals for a firewall. evaluate 5 3 Discuss in short about Viruses create 6 4 Explain in detail about virus understand 1 5 List the different types of firewall and its configurations Understand 1

9.13 TUTORIAL QUESTION BANK (5/UNIT) PART A (SHORT ANSWER QUESTIONS) S.No Questions Blooms Course Taxonomy Outcome level

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UNIT-I 1 Explain the two basic ways of transforming plain text to cipher text. Understand 1 2 Differentiate between substitution cipher and transposition cipher Analyze 4 3 Differentiate between a mono alphabetic cipher and poly alphabetic cipher? Analyze 4 4 Explain Steganography Understand 1 5 Explain the basic functions used in encryption Understand 1 algorithms? UNIT- II 1 Substitute Bytes Transformation create 6 2 What is the role of S-Box in DES? Remember 1 3 Discuss the design principles of block cipher technique? Analyze 4 4 What is a Feistel Cipher? Remember 1 5 Give the structure of AES. Analyze 4 UNIT- III 1 What are the requirements of cryptographic hash evaluate functions?. 5 2 What are the attacks that are possible on RSA? Remember 1 3 What are the requirements of Kerberos? analyze 3 4 Define MAC (Message Authentication Code). Remember 1 5 Write short notes on Digital Signature Algorithm create 6 UNIT- IV 1 What is meant by IP Spoofing? Remember 1 2 What is S/MIME? Understand 1 3 What are the keys used by PGP? Remember 1 4 What is e-mail security? Explain the technique for e- Remember 1 mail security? 5 What is the role of Key Distribution centre? Understand 1 UNIT- V 1 What is inter function call? Remember 1 2 What are the different combinations of Security Understand 1 Association on a network? 3 What are the contents of a Security Association? Understand 1 4 Sketch neatly the SSL protocol stack. Remember 1 5 What are the basic approaches of building Security Understand 1 Associations?

9.14 TUTORIAL QUESTION BANK (5/UNIT) PART B(LONG ANSWER QUESTIONS) S.No Questions Blooms Course Taxonomy level Outcome UNIT-I Determine the security mechanisms required to Remember 1 1 provide various types of security services. Write briefly the categories of attacks. What are the 2 Remember 1 x.800 listed attacks? 3 What are the different transposition techniques? Explain Understand 3

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4 Explain Hill cipher with an example. Understand 5 5 Explain Network security model with neat diagram. Understand 1 UNIT- II 1 Explain in detail about the steps involved in DES. create 6 How do you convert a block cipher into a stream 2 cipher by using the Cipher Feedback (CFB) mode? Remember 1 Explain. What are the various block cipher design principles? 3 Explain how different cryptographic algorithms use Analyze 4 Fiestel Cipher Structure? Which four tasks are performed in each round of 4 Remember 1 AES Cipher? Explain. Define OFB and list its advantages and 5 Analyze 4 disadvantages UNIT- III What is the cipher text if the plain text is 63 and 1 evaluate public key is 13? Use RSA algorithm. 5 Briefly explain the Diffie Hellman Key Exchange 2 Remember algorithm? 1 Give the structure of HMAC. Explain the applications of 3 analyze HMAC. 3 What are discrete logarithms? Explain how are they 4 Remember used in Public Key Cryptography? 1 Give the structure of SHA-512 compression 5 function. Explain the structure of each round. Is Man create 6 in the Middle attack possible on SHA-512 UNIT- IV Give the summary of cryptographic algorithms used by Remember 1 S/MIME 1 Describe the process involved in digital signatures. 2 Understand Explain about different digital signatures. 1 3 What are the main features of Kerberos Version 5? Remember 1 4 Explain about Pretty Good Privacy (PGP). Remember 1 5 Describe the architecture of IPSec. Understand 1 UNIT- V Explain the methods used for statistical anomaly 1 Remember detection. 1 Write briefly about the signature based Intrusion 2 Understand 1 Detection Systems. 3 Explain about SSL Handshake protocol. Understand 1 What is an audit record? What is the use of audit record in 4 Remember intrusion detection? 1 What are the different combinations of Security 5 Understand 1 Association on a network?

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10. CLOUD COMPUTING (A70519)

10.0 COURSE DESCRIPTION

Course Title CLOUD COMPUTING Course Code A10540 Regulation MLR15 Lectures Tutorials Practical Credits Course Structure 3 1 - 3 Course Coordinator Dr. N.V. Rajasekhar Reddy,Professor, CSE Mr. P. Ram Mohan Rao, Assoc. Professor, CSE Team of Instructors Mrs. V. Prashanthi, Asst. Professor, CSE Mr. V. Aadarsh, Asst. Professor, CSE

10.1 COURSE OVERVIEW:

The course is designed to give introduction to modern distributed computing. It describes in detail, methods of accessing computing resource across the internet. The course will also explain the relevance of these forms of computing to business models for enterprises that require large amounts of computation but do not necessarily wish to purchase and maintain large amounts of specialist computing systems.

10.2 PREREQUISITES:

Level Credits Periods/Weeks Prerequisites UG 3 4 Computer Networks

10.3 MARKS DISTRIBUTION:

University End Total Session Marks (25M) Exam Marks Marks Mid Semester Test There shall be two midterm examinations.Each midterm examination consists of subjective type and objective type tests. The subjective test is for 10 marks of 60 minutes duration. Subjective test shall contain 4 questions; the student has to answer 2 questions and each carrying 5 marks. The objective type test is for 10 marks of 20 minutes duration. It consists of 10 Multiple choice and 10 objective type questions, the 75 100 student has to answer all the questions and each carries half mark. First midterm examination shall be conducted for the first two and half units of syllabus and second midterm examination shall be conducted for the remaining portion. Assignment Five marks are earmarked for assignments.There shall be two assignments in every theory course. Marks shall be awarded considering the average of two assignments in each course.

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10. 4EVALUATION SCHEME:

S. No Component Duration Marks

1. I Mid Examination 80 minutes 20

2. I Assignment --- 5

3. II Mid Examination 80 minutes 20

4. II Assignment ---- 5

5. External Examination 3 hours 75

10.5 COURSE OBJECTIVES:

1. To introduce Distributed System Models and its related technologies. 2. To introduce Cloud Computing Service Models, Architecture and Management. 3. To familiarize the concept of Service Oriented Architectures. 4. To teach the real-time cloud computing software environments. 5. To teach Grid Computing Systems and Resource Management.

COURSE OUTCOMES:

At the end of the course students will able to:

A. Understand the Distributed Systems and related technologies. B. Understand the Cloud Service Models and can design cloud platforms. C. Learn the Service Oriented Architectures and workflows. D. Work with real-time Cloud Software environments. E. Learn Grid Computing systems and Resource Management.

10.6 HOW PROGRAM OUTCOMES ARE ASSESSED:

Proficiency Program Outcomes Level assessed by An ability to apply the knowledge of mathematics, Computing, Assignments, A Science and engineering to solve Computer Science and Engineering H Tutorials, Exams problems An ability to design and conduct engineering experiments, as well as B S Assignments, tutorials to analyze and interpret data. An ability to design and construct a hardware and software system, C component, or process to meet desired needs, within realistic H Assignments, Tests constraints Graduates will demonstrate an ability to visualize and work on D laboratory and Multi-disciplinary tasks individually or as a member N ------within the teams An ability to demonstrate skills to use the techniques, modern E engineering Tools, Software and equipment necessary to analyze H Assignments, Tests computer engineering Problems

F An understanding of professional, social and ethical responsibility S Lectures

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An ability to recognize the global issues like green initiatives and G alternate energy sources and to take technology to villages and to S ------recognize the rural requirements The broad education necessary to understand the impact of H engineering solutions in a global, economic, environmental, and N Lectures societal context Graduate will develop confidence for self-education and acquire new Assignments, I knowledge in the computing discipline and ability and practice for H Tutorials, Exams Multi-disciplinary tasks as a member within the teams Assignments, J To communicate effectively N Tutorials, Exams

An ability to use the techniques, skills and modern engineering tools Assignments, K H necessary for Engineering practice Tutorials, Exams

Graduates are able to participate and succeed in competitive Assignments, L N examination like GRE, GATE, TOEFL, GMAT etc. Tutorials, Exams The use of current application software and the design and use of operating systems and the analysis, design, testing and documentation Assignments, M H of computer programs for the use in Computer Science and Tutorials, Exams engineering technologies. N=None S=Supportive H=Highly Related

10.7 SYLLABUS:

UNIT- I

DISTRIBUTED SYSTEM MODELS AND ENABLING TECHNOLOGIES: Scalable Computing Service over the Internet, The Age of Internet Computing, Computing Trends and New Paradigms. System Models for Distributed and Cloud Computing, Clusters of Cooperative Computers, Grid Computing Infrastructures, Peer- to-Peer Network Families, Cloud Computing over the Internet. Software Environments for Distributed Systems and Clouds, Service-Oriented Architecture (SOA), Distributed Operating Systems and Software Tools, Parallel/Distributed Programming Models. Performance, Security and Energy-Efficiency: Performance Metrics and Scalability Analysis, Fault-Tolerance and System Availability, Network Threats and Data Integrity, Energy-Efficiency in Distributed Computing.

UNIT - II

DESIGN OF CLOUD COMPUTING PLATFORMS: Cloud Computing and Service Models; Public, Private and Hybrid Clouds, Cloud Ecosystem and Enabling Technologies, Infrastructure-as-a-Service (IaaS) Model, Platform -and Software-as-a-Service (Paas, SaaS). Architecture Design Of Compute And Storage Clouds: A Generic Cloud Architecture Design, Layered Cloud Architectural development, Virtualization Support and Disaster Recovery, Architectural Design Challenges. Public Cloud Platforms: Google Application Engine (GAE), Amazon Web Service (AWS) and Windows Azure; Public Clouds and Service Offerings, Google Application Engine (GAE), Amazon Web Service (AWS), Microsoft Windows Azure. Inter- Cloud Resource Management: Extended Cloud Computing Services, Resource Provisioning and Platform Deployment, Virtual Machine Creation and Management, Global Exchange of Cloud Resources. Cloud Security and Trust Management: Cloud Security Defence Strategies, Distributed

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Intrusion/Anomaly Detection, Dataand Software Protection Techniques, Reputation-Guided Protection of Datacenters.

UNIT - III SERVICE ORIENTED ARCHITECTURES: Services and Service Oriented Architectures:REST and Systems of Systems,Services and Web Services, Enterprise Multi-tier Architecture, Grid Services andOGSA, Other Service Oriented Architectures and Systems. Message-Oriented Middleware: Enterprise Bus, Publish-Subscribe Model and Notification, Queuing and Messaging Systems, Cloud and Grid Middleware applications. Discovery, Registries,Metadata and Databases: UDDI and Service Registries, Databases and Publish-Subscribe, Metadata catalogues,Semantic Web and Grid, Job Execution Environments and Monitoring. Workflow in Service-Oriented Architectures: Basic Concepts of Workflow, Workflow Standards, Workflow Architecture and Specification, Workflow Execution Engine UNIT - IV CLOUD PROGRAMMING AND SOFTWARE ENVIRONMENTS: Features of Cloud Platforms. Cloud Capabilities and Platform Features, Traditional Features Common to Grids and Clouds, Data Features and Databases, Programming and Runtime Features. Parallel and Distributed Programming Paradigms; Parallel Computing and Programming Paradigms, Map Reduce, Twister and Iterative Map Reduce, Hadoop Library from Apache, Mapping Applications to Parallel and Distributed Systems. Programming Support of Google App Engine: Programming the Google App Engine, Google File System (GFS), Big table, Google‘s NOSQL system, Chubby, Google‘s Distributed Lock service. Programming on Amazon AWS and Microsoft Azure: Programming on Amazon EC2, Amazon Simple Storage Service S3, Amazon Elastic Block Store EBS and SimpleDB, Microsoft Azure programming support. EMERGING CLOUD SOFTWARE ENVIRONMENTS: Open Source Eucalyptus and Nimbus, Open Nebula, Sector/Sphereand OpenStack, Manjrasoft Aneka Cloud and Appliances. UNIT - V GRID COMPUTING SYSTEMS AND RESOURCE MANAGEMENT: Grid Architecture and Service Modeling Grid History and service families, CPU Scavenging and Virtual super computers, OGSA, Data intensive Grid service models. GRID RESOURCE MANAGEMENT AND BROKERING: Resource Management and Job Scheduling, Grid ResourceMonitoring with CGSP, Service Accounting and Economy Model, Grid Resource Brokering with Gridbus. Software and Grid Computing; Open-Source Grid Middleware Packages, The Globus Toolkit Architecture (GT4), Containers and Resource/Data Management.Grid Application Trends and security measures; Trust models for grid security enforcement, Authentication and Authorization methods, GSI. On-Line Social and Professional Networking; Online Social Network Characteristics, Graph-Theoretic Analysis of Social networks, Communities and Applications of Social Networks, Facebook: The World‘s Largest Content-Sharing Network, Twitter for Micro blogging, News and Alert Services. TEXT BOOKS: 1. Kai Hwang, Jack Dongarra, Geoffrey Fox (2011), Distributed and Cloud Computing, From Parallel Processing tothe Internet of Things, Morgan Kaufman Publishers, India. REFERENCE BOOKS: 1. Joshy Joseph, Craig Fellenstein (2007), Grid Computing, IBM Press, India. 2. Prabhu (2007), Grid and Cluster Computing, Prentice Hall of India, New Delhi.

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3. Anthony T. Velte, Toby J. Velte, Robert Elsenpeter (2010), Cloud Computing, A Practical Approach, McGraw Hill Edition, New Delhi.

10.8 COURSE PLAN:

Course Lecture Blooms S.No. Learning Topics to be covered Reference No Level Outcomes Understand the system models for Understand Distributed system models and 1 1 T1:Ch1.1- distributed [Level 2] enabling technologies and cloud computing Analyze the classifications Scalable Computing Service Analyze 2 of parallel and 2 over the Internet, the Age of T1:Ch1.1.1 [Level 4] distributed Internet Computing systems Apply various network technologies based systems Apply Scalable Computing Trends and 3 and to reduce 3 T1:Ch1.1.2 [Level 3] New Paradigms the design time and improve the speed Analyze various cluster Analyze Internet of Things and Cyber- 4 network 4 T1:Ch1.1.3 [Level 4] Physical Systems. technologies based systems Identify various network technologies System Models for Distributed and based systems Identify 5 5 Cloud Computing, Clusters of T1:Ch1.3 and to reduce [Level 4] Cooperative Computers the design time and improve the speed. List out the design List Grid Computing Infrastructures, T1:Ch1.3.2- 6 objectives of 6 [Level 1] Peer-to-Peer Network Families, 1.3.3 computer cluster

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Evaluate the cluster job management system Evaluate 7 7 Cloud Computing over the Internet T1:Ch1.3.4 through job [Level 5] scheduler and resource manager. Implement various levels of functional Software Environments for Implement T1:Ch1.4- 8 layers of 8 Distributed Systems and Clouds- [Level 6] 1.4.1 hardware or SOA software resources Apply the various configurations Trends toward distributed operating Apply 9 of the 9 systems, Parallel and distributed T1:Ch1.4.2 [Level 3] software and programming models hard ware tools. Identify Performance, Security and Energy- various Identify 10 10 Efficiency: Performance Metrics T1:Ch1.5.1 security [Level 4] and Scalability Analysis . related issues. Analyze the Fault-Tolerance and System network T1:Ch1.5.2- 11 11 Analyze availability Network Threats and threats in the 1.5.3 [Level 4] Data Integrity cloud. Interpret the energy issues Interpret Energy-Efficiency in Distributed 12 12 T1:Ch1.5.4 in Distributed [Level 2] Computing systems. Design the cloud Design Design of cloud computing 15 13 T1:Ch4 computing [Level 6] platforms platform. Differentiate various types Differentiate Cloud Computing and Service 16 14 T1:Ch4.1 of clouds [Level 2] Models computing. Identify Cloud Ecosystem and Enabling different types Identify T1:Ch4.1.2- 17 15 Technologies, Infrastructure-as-a- of clouds in [Level 4] 4.1.3 Service (IaaS) Model Iaas. Understand Platform-as- a- Understand 18 framework of 16 service(PaaS),software-as- a- T1:Ch4.1.4 [Level 2] PaaS service(SaaS)

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Analyze the Analyze Architecture Design Of Compute 19 framework of 17 T1:Ch4.3 [Level 4] And Storage Clouds SaaS Identify virtual resources such Identify Layered Cloud Architectural 20 18 T1:Ch4.3.2 as servers, [Level 4] development storage, and networks Understand management data center Understand Virtualization Support and Disaster 21 19 T1:Ch4.3.3 team by [Level 2] Recovery system configuration Analyze the use of virtualization Analyze 22 20 Architectural Design Challenges T1:Ch4.3.4 management [Level 4] data center team Identify the Public Cloud Platforms,Google 23 seven –step 21 Identify T1:Ch4.4 Application Engine (GAE), models [Level 4] Demonstrate 24 the use of 22 Demonstrate AWS, Microsoft Windows Azure T1:Ch4.4.3 AWS [Level 2] Illustrate the inter cloud Inter- Cloud Resource 25 resource 23 Illustrate Management: Extended Cloud T1:Ch4.5 management [Level 2] Computing Services system. Create a Virtual Machine Creation and T1:Ch4.5.3- 26 virtual 24 Create Management, Global Exchange 4.5.4 machine [Level 6] of Cloud Resources Interpret the Cloud Security and Trust cloud security 27 25 Interpret Management: Cloud Security T1:Ch4.6 defense [Level 2] Defense Strategies strategies Examine the data and Examine Data and Software Protection 28 software 26 T1:Ch4.6.3 [Level 4] Techniques protection techniques. Services and Service Oriented Summarize Summarize Architectures: REST and Systems T1:Ch5.1- 31 27 the SOA [Level 4] of Systems, Services and Web 5.1.2 Services Discuss the Discuss 32 28 Enterprise Multi-tier Architecture T1:Ch5.1.3 multi-tier [Level 6]

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architecture

To understand Grid Services and OGSA, Other understand T1:Ch5.1.4- 33 architecture of 29 Service Oriented Architectures and [Level 2] 5.1.5 grid services. Systems Demonstrate the message Demonstrate 34 oriented 30 Message-Oriented Middleware T1:Ch5.2 [Level 2] middle strategies. Understand

queuing and 35 31 Understand Queuing and Messaging Systems. T1:Ch5.2.3 messaging [Level 2] systems. Analyze the Discovery, Registries, Metadata concept the Analyze 36 32 and Databases-UDDI and service T1:Ch5.4 metadata and [Level 4] registers databases Create metadata Create Metadata catalogues, Semantic T1:Ch5.4.3- 37 catalog and 33 [Level 6] Web and Grid, 5.4.4 semantic web pages. Examine the Examine Job Execution Environments and 38 job execution 34 T1:Ch5.4.5 [Level 4] Monitoring environment. Understand Understand Workflow in Service- Oriented 39 the concept of 35 T1:Ch5.5 [Level2] Architectures SOA Evaluate the workflow Evaluate 40 36 Workflow Execution Engine T1:Ch5.5.4 execution [Level 5] engine. Analyze and write Analyze Cloud programming and software 42 programs on 37 T1:Ch6 [Level 4] environments cloud programming. List the cloud capabilities List Cloud capabilities and platform 43 38 T1:Ch6.1 and platform [Level 1] features features. Discuss parallel computing Discuss Parallel Computing and 44 39 T1:Ch6.2 and [Level 6] Programming Paradigms programming paradigms Categorize Categorize Data Features and Databases, 45 40 T1:Ch6.2.1 different data [Level 4] MapReduce,

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features and databases Evaluate the Evaluate 46 mapreduce 41 Twister and Iterative MapReduce T1:Ch6.2.1 [Level 5] algorithms Examine the Examine 47 Hadoop 42 Hadoop Library from Apache T1:Ch6.2.3 [Level 4] library Compare mapping applications of Compare Mapping Applications to Parallel 48 43 T1:Ch6.2.6 Parallel and [Level 3] and Distributed Systems Distributed systems. Determine the Programming Determine Programming Support of Google 49 Support of 44 T1:Ch6.3 [Level 4] App Engine Google App Engine Create google Create 50 45 Google File System (GFS) T1:Ch6.3.2 file systems [Level 6] Compare google Compare Bigtable, Google‘s NOSQL 51 46 T1:Ch6.3.3 NOSQL and [Level 3] system, Chubby Chubby. Slove Programs on Slove Programming on Amazon AWS 52 Amazon AWS 47 T1:Ch6.4 [Level 6] and Microsoft Azure and Microsoft Azure Classify Amazon Simple Storage Service different Classify 53 48 S3, Amazon Elastic Block Store T1:Ch6.4.2 Amazon [Level 4] EBS and SimpleDB services. Interpret different cloud Interpret Emerging cloud software 54 59 T1:Ch6.5 software [Level 2] environments environments. Understand Open Nebula Understand Open Nebula, Sector/Sphere and T1:Ch6.5.1- 55 50 and Open [Level 2] Open Stack 6.5.2 Stack Examine Manjra soft Examine Manjra soft Aneka Cloud and 56 Aneka Cloud 51 T1:Ch6.5.3 [Level 4] Appliances and Appliances Evaluate Grid Evaluate Grid Architecture and Service 59 Architecture 52 T1:Ch7.1 [Level 5] Modeling and Service

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Modeling

Differentiate CPU Scavenging Differentiate CPU Scavenging and Virtual super 60 53 T1:Ch7.1.2 and Virtual [Level 2] computers super computers Examine the different grid Examine OGSA, Data intensive Grid service 61 54 T1:Ch7.1.3 service [Level 4] models. models. Evaluate Resource Evaluate Resource Management and Job 62 Management 55 T1:Ch7.3 [Level 5] Scheduling and Job Scheduling Understand Grid Resource Monitoring with Understand T1:Ch7.3.2- 63 Grid Resource 56 CGSP,Service Accounting and [Level 2] 7.3.3 Monitoring Economy Model Analyze Resource Brokering Resource Brokering with Analyze 64 with Gridbus, 57 Gridbus,Software and Grid T1:Ch7.3.4 [Level 4] Software and Computing Grid Computing Understand Understand The Globus Toolkit Architecture 65 architecture of 58 T1:Ch7.4 [Level 2] (GT4) GT4 Determine Data Determine Containers and Resource/Data 66 59 T1:Ch7.4.3 Management [Level 4] Management strategies Identify the Identify Grid Application Trends and 67 security 60 T1:Ch7.5 [Level 4] security measures measures. Compare the trust modles Compare Trust models for grid security 68 61 T1:Ch7.5.3 of grid [Level 3] enforcement security. Identify the Authentication Identify Authentication and Authorization T1:Ch7.5.4- 69 and 62 [Level 4] methods, GSI 7.5.5 Authorization methods Examine the Examine On-Line Social and Professional 70 online social 63 T1:Ch9.5 [Level 4] Networking networking

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Compare Graph- Theoretic Compare Graph-Theoretic Analysis of Social 71 64 T1:Ch9.5.2 Analysis of [Level 3] networks Social networks Identify the Communities and Identify Communities and Applications of T1:Ch9.5.3- 72 Applications 65 [Level 4] Social Networks, Facebook 9.5.4 of Social Networks, Facebook

10.9 MAPPING COURSE OBJECTIVE LEADING TO THE ACHIEVEMENT OF COURSE OUTCOMES: Course Outcomes Course Objective 1 2 3 4 5 1 H H S S H 2 H H S S H 3 H S H S S 4 S H S H S 5 S S S S H S=Supportive H=Highly Related

10.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES: Program Outcomes Course Outcomes A B C D E F G H I J k L M

1 H H H S H H H S H H

2 S H S S H S S H S

3 H H H H H H H H

4 H H H S H H H S H H

5 S H S S H H S S H H S=Supportive H=Highly Related

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10.11 OBJECTIVE BITS: UNIT-I 1. HPC Systems are inherited from one the following A. Clusters B. MPP C. P2P networks D. None Answer A and B 2. The distributed file sharing and content delivery applications are performed by A. Clusters B. MPP C. P2P networks D. none Answer C 3. The computing paradigm internet of clouds is achieved by A. Clusters B. Virtualization C. Distributed D. Parallel Answer B 4. __ is evolved from the convergence of MEMs, internet and wireless technology A. Cloud B. Clusters C. P2P network D. IOT Answer D 5. The reduction of power consumption and performance, processing of multiple tasks achieved by A. MPP B. Multicore CPUs C. HPC D. HTC Answer B 6. A network which build and runs on top of another succeeded network A. Overlay B. P2P C. CDNs D. SAN Answer A 7. The __are built with virtual machines installed from one or more physical clusters A. EC2 B. Virtual clusters C. Xen servers D. VMs Answer B 8. One of the following is technique in intrusion detection system A. Honey pot B. Hypervisor C. V sphere D. None Answer A 9. Intrusion detection system types are A. IDS B. HIDS C. NIDS D. None Answer B&C 10. Network migration can performed A. Offline B. Online

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C. Live D. None Answer B&C 11. OGSA stands for A. Open Grid Service Architecture B. Open Graphic service Architecture C. Open Grid Satellite Architecture D. None Answer: A 12. One of the following is a feature of OGSA A. BKI B. PKI C. Both D. None Answer: B 12. Objectives in distributed applications. A. Data locality B. interoperability C. network proximity D. All the above Answer: D 13. An elastic and flexible computing environment that allows web application developers to acquire cloud resources effectively A. Napster B. EC2 C. REST D. None Answer: B 14. After virtualization, a virtualization layer is inserted between A. Hardware and os B. Software and os C. Host and os D. None Answer: A 15. VMM is known as A. Virtual Machine Management B. Virtual Machine Monitor C. Virtual Machine Manufacturer D. None Answer: B 16. KVM is a hardware-assisted para-virtualization tool, which improves performance and supports unmodified guest OSes A. Windows B. Linux C. Solaris D. All the above Answer: D 17. A VM is a duplicate of an existing computer system in which a majority of the VM instructions are executed on the host processor in A. Native mode B. Privileged mode C. Unprivileged mode D. None Answer: A 18. __is a good example of a web service that provides elastic computing power in a cloud A. Amazon’s Elastic Compute Cloud (EC2) B. IBM Web service C. Salesforce D. None

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Answer: A 19. The Internet Suspend-Resume (ISR) technique exploits temporal locality as A. Memory B. States C. Memory states D. Process states Answer: C 20. ___ is built on operating systems, and is based on the characteristicsof intrusion actions A. IDS B. VM C. VMM D. None Answer: A

UNIT -2 1. Point out the wrong statement: a) Amazon Machine Instances are sized at various levels and rented on a computing/hour basis b) The metrics obtained by CloudWatch may be used to enable a feature called Auto Scaling c) A Number of tools are used to support EC2 services d) None of the mentioned Answer: d 2. Which of the following is an edge-storage or content-delivery system that caches data in different physical locations ? a) Amazon Relational Database Service b) Amazon SimpleDB c) Amazon Cloudfront d) Amazon Associates Web Services Answer: c 3. Which of the following allows you to create instances of the MySQL database to support your Web sites ? a) Amazon Elastic Compute Cloud b) Amazon Simple Queue Service c) Amazon Relational Database Service d) Amazon Simple Storage System Answer: c 4. Point out the correct statement: a) Amazon Elastic Cloud is a system for creating virtual disks(volume) b) SimpleDB interoperates with both Amazon EC2 and Amazon S3 c) EC3 is an Analytics as a Service provider d) None of the mentioned Answer: b 5. Which of the following is a structured data store that supports indexing and data queries to both EC2 and S3 ? a) CloudWatch b) Amazon SimpleDB c) Amazon Cloudfront d) All of the mentioned Answer: b 6. Which of the following is the machinery for interacting with Amazon’s vast product data and eCommerce catalog function ? a) Amazon Elastic Compute Cloud b) Amazon Associates Web Services c) Alexa Web Information Service d) All of the mentioned Answer: b 7. Which of the following is a billing and account management service ? a) Amazon Elastic MapReduce b) Amazon Mechanical Turk c) Amazon DevPay

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d) Multi-Factor Authentication Answer: c 8. Which of the following is a means for accessing human researchers or consultants to help solve problems on a contractual or temporary basis ? a) Amazon Elastic MapReduce b) Amazon Mechanical Turk c) Amazon DevPay d) Multi-Factor Authentication Answer: b 9. Which of the following is built on top of a Hadoop framework using the Elastic Compute Cloud ? a) Amazon Elastic MapReduce b) Amazon Mechanical Turk c) Amazon DevPay d) Multi-Factor Authentication Answer: a 10. Which of the following is owned by an organization selling cloud services ? a) Public b) Private c) Community d) Hybrid Answer: a 11. Point out the wrong statement : a) Everything from the application down to the infrastructure is the vendor’s responsibility b) In the deployment model, different cloud types are an expression of the manner in which infrastructure is deployed c) AaaS provides virtual machines, operating systems, applications, services, development frameworks, transactions, and control structures d) All of the mentioned Answer: c 12. ______provides virtual machines, virtual storage, virtual infrastructure, and other hardware assets a) IaaS b) SaaS c) PaaS d) All of the mentioned Answer: a 13. Which of the following provides development frameworks and control structures ? a) IaaS b) SaaS c) PaaS d) All of the mentioned Answer: c 14. Point out the wrong statement : a) A PaaS service adds integration features, middleware, and other orchestration and choreography services to the IaaS model b) XaaS or ‘anything as a service’ is the delivery of IT as a Service through hybrid Cloud computing c) Monitoring as a Service (MaaS) is at present still an emerging piece of the Cloud jigsaw d) None of the mentioned Answer: d 15. ______is a complete operating environment with applications, management, and the user interface. a) IaaS b) SaaS c) PaaS d) All of the mentioned Answer: b

16. How many types of service model are mainly present in Cloud ?

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a) 1 b) 2 c) 3 d) 4 Answer: c 17. The three different service models is together known as the _____ model of cloud computing. a) SPI b) SIP c) CPI d) All of the mentioned Answer: a 18. CaaS stands for ______as a service. a) Compliance b) Computer c) Community d) Communication Answer: d 19. Which of the following is IaaS service provider ? a) EC2 b) EC1 c) EC10 d) Hybrid Answer: a

20. Which of the following is most complete cloud computing service model ? a) PaaS b) IaaS c) CaaS d) SaaS Answer: d

UNIT 3

1. Which of the following describes a message-passing taxonomy for a component-based architecture that provides services to clients upon demand ? a) SOA b) EBS c) GEC d) All of the mentioned Answer: a 2. Point out the correct statement: a) Service Oriented Architecture (SOA) describes a standard method for requesting services from distributed components and managing the results b) SOA provides the translation and management layer in an architecture that removes the barrier for a client obtaining desired services c) With SOA, clients and components can be written in different languages and can use multiple messaging protocols d) All of the mentioned Answer: d 3. Which of the following is a repeatable task within a business process ? a) service b) bus c) methods d) all of the mentioned Answer: a 4. Point out the wrong statement: a) SOA provides the standards that transport the messages and makes the infrastructure to support it possible b) SOA provides access to reusable Web services over a SMTP network

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c) SOA offers access to ready-made, modular, highly optimized, and widely shareable components that can minimize developer and infrastructure costs d) None of the mentioned Answer: b 5. Which of the following is used to define the service component that performs the service ? a) WSDL b) SCDL c) XML d) None of the mentioned Answer: b 6. Which of the following is commonly used to describe the service interface, how to bind information, and the nature of the component’s service or endpoint ? a) WSDL b) SCDL c) XML d) None of the mentioned Answer: a 7. Which of the following provides commands for defining logic using conditional statements ? a) XML b) WS-BPEL c) JSON d) None of the mentioned Answer: b 8. Which of the following vendor is offering optimization appliances for VMware’s infrastructure ? a) Expand Networks b) Certeon c) Replify d) None of the mentioned Answer: b 9. Point out the correct statement : a) Virtual appliances are a relatively new paradigm for application deployment b) External network virtualization cannot be done using network switches and VLAN software c) All imaging programs can take snapshots of systems d) All of the mentioned Answer: a 10. Simple Cloud API is useful for applications written in : a) PHP b) Python c) Scala d) None of the mentioned Answer: a 11. The ______solution creates a virtual application appliance as an architectural layer between the Windows or the UNIX operating system and applications. a) AppOne b) AppZero c) AppSoft d) None of the mentioned Answer: b 12. Point out the wrong statement : a) Cloud computing applications have the ability to run on virtual systems b) Systems (VMs running applications), storage, and network assets cannot be virtualized c) Applications that run in datacenters are captive to the operating systems and hardware platforms that they run on d) All of the mentioned Answer: b 13. ______creates a container that encapsulates the application and all the application’s dependencies within a set of files. a) VAA b) VAS c) VSA

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d) None of the mentioned Answer: a 14. Which of the following layer serves as the mediator for file I/O, memory I/O, and application calls and response to DLLs ? a) application b) client c) virtualization d) None of the mentioned Answer: c 15. Which of the following application delivery platform’s main focus is on desktop installations ? a) Microsoft App-V b) Microsoft Hyper c) Amazon EC2 d) All of the mentioned Answer: a 16. Which of the following is most widely used technique for abstraction ? a) Load balancing b) Load scheduling c) Load scaling d) All of the mentioned Answer: a 17. Which of the following is a potent cloud-building technology ? a) vSphere b) HyperCube c) vCube d) All of the mentioned Answer: a 18. Which of the following backup lets you restore your data to a point in time and saves multiple copies of any file that has been changed ? a) Point-in-time b) Differential c) Reverse backup d) None of the mentioned Answer: a 19. The amount of time needed to backup a system is referred to as its: a) backup time b) backup sheet c) backup window d) all of the mentioned Answer: c 20. Which of the following element is used by orchestrated business process commonly referred as ? a) conductor b) coordinator c) orchestrator d) all of the mentioned Answer: c

UNIT 4

1. Which of the following service creates an application hosting environment? a) EBS b) Azure AppFabric c) ESW d) All of the mentioned Answer: b 2. Point out the wrong statement: a) Microsoft’s approach is to view cloud applications as software plus service b) Microsoft calls their cloud operating system the Windows Platform c) Azure is a combination of virtualized infrastructure to which the .NET Framework has been added as a set of .NET Services

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d) None of the mentioned Answer: d 3. Which of the following is also known as Compute ? a) set of virtual machine instances b) set of replicas c) set of commodity servers d) all of the mentioned Answer: a 4. Database marketplace based on SQL Azure Database is code-named ______. a) Akamai b) Dallas c) Denali d) None of the mentioned Answer: b

5. Point out the correct statement: a) The Windows Azure service itself is a hosted environment of virtual machines enabled by a fabric called Windows Azure ApplicationFab b) Windows Azure service is a Compliance as a Service offering c) Windows Live Services is a collection of applications and services that run on the Web d) All of the mentioned Answer: c 6. ______Live Services can be used in applications that run in the Azure cloud. a) Microsoft b) Windows c) Yahoo d) Ruby Answer: b

7. Which of the following is based on Microsoft Dynamics ? a) Static CRM b) Social CRM c) Dynamics CRM d) None of the mentioned Answer: c 8. Which of the following is based on Microsoft Sharepoint ? a) Sharepoint Services b) .NET Services c) Windows Services d) All of the mentioned Answer: a 9. Azure is Microsoft’s ______as a Service Web hosting service. a) Platform b) Software c) Infrastructure d) All of the mentioned Answer: c 10. Which of the following is a pure infrastructure play ? a) Azure b) Google App Engine c) AWS d) None of the mentioned Answer: c 11. Which of the following algorithm is used by Google to determine the importance of a particular page ? a) SVD b) PageRank c) FastMap d) All of the mentioned Answer: b

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12. Point out the correct statement : a) With PaaS, the goal is to create hosted scalable applications that are used in a Software as a Service model b) Applications built using PaaS tools need to be standards-based c) In Wolf, the data and transaction management conforms to the business rules you create d) All of the mentioned Answer: d 13. Based on PageRank algorithm, Google returns ______for a query that is parsed for its keywords. a) SEP b) SAP c) SERP d) Business Objects Build Answer: c 14. Point out the wrong statement: a) Wolf Frameworks uses a C# engine and supports both Microsoft SQL Server and MySQL database b) Applications built in Wolf are 50-percent browser-based and support mashable and multisource overlaid content c) Google applications are cloud-based applications d) None of the mentioned Answer: b 15. Which of the following protocol lets a Web site list in an XML file information ? a) Sitemaps b) Mashups c) Hashups d) All of the mentioned Answer: a 16. Which of the following is not privided by “Deep Web” ? a) Database generated Web pages b) Private or limited access Web pages c) Pages without links d) All of the mentioned Answer: d 17. Dynamic content presented in Google ______crawling isn’t normally indexed. a) AJAX b) Java c) Javascript d) All of the mentioned Answer: a

18. Which of the following google product sends you periodic email alerts based on your search term ? a) Alerts b) Blogger c) Calendar d) All of the mentioned Answer: a 19. Which of the following is a payment processing system by Google ? a) Paytm b) Checkout c) Code d) All of the mentioned Answer: b 20. Which of the following creates a custom search utility for a particular Web site ? a) Desktop b) Directory c) Custom Search d) None of the mentioned Answer: c

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UNIT 5

1. Which of the following is a search service for online retailers that markets their products in their site searches with a number of navigation ? a) Google Site Search b) Google Commerce Search c) Google Search Appliance d) Google Mini Answer: b 2. Point out the correct statement : a) Google Bookmarks is a detailed 3D model of the human body b) Google Base is an online service that lets you save your favorite sites and attach labels and comments c) The Chromium projects include Chromium and Chromium OS d) All of the mentioned Answer: c 3. Which of the following can be deployed within an organization to speed up both local (Intranet) and Internet searching ? a) Google Site Search b) Google Commerce Search c) Google Search Appliance d) Google Mini Answer: c

4. Which of the following is the smaller version of the GSA that stores 300,000 indexed documents ? a) Google Site Search b) Google Big Search c) Google Search Appliance d) Google Mini Answer: d 5. Point out the wrong statement: a) With Google Custom Search Engine and Subscribed Links, you can create a search engine tailored to your needs b) Google Currents is a social magazine app by Google c) Google Correlate is a social magazine app by Google d) None of thementioned Answer: c 6. Which of the following is a targeted ad service based on matching advertisers and their keywords to users and their search profiles ? a) Ads b) AdSense c) AdWords d) All of the mentioned Answer: c 7. Google ______is the most widely used Web traffic analysis tool on the Internet. a) BigAnalytics b) Analytics c) Biglytics d) All of the mentioned Answer: b 8. Which of the following system was replaced with Google Translate ? a) SYSTRANSMIT b) SYSTRAN c) SYSTRANFER d) None of the mentioned Answer: b 9. Which of the following service that provides offline access to online data ? a) Gears

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b) Blogger c) Offline d) All of the mentioned Answer: a 10. Which of the following is an open-source platform that has been used to create Google Wave and Google AdWords ? a) GWT b) GET c) GTW d) All of the mentioned Answer: a 11. Which of the following is a specific top-level domain created for the producers and consumers of mobile services ? a) MOB b) .MOBI c) CELL d) None of the mentioned Answer: a 12. Point out the wrong statement: a) Mobile phones are differentiated into feature phones and smartphones b) Cloud computing offers the capability to run cell phone applications and Web services and to store data remotely c) The eventual impact of the cloud on mobile devices will be to make them thicker(as client) d) All of the mentioned Answer: c 13. Which of the following domain is used to create sites that render correctly on mobile devices? a) Mobile Top Level Domain b) Mobile Middle Level Domain c) Mobile Low Level Domain d) All of the mentioned Answer: a 14. Which of the following tool analyzes Web sites and scores them by dotMobi ? a) Ready mobi b) Call mobi c) Push mobi d) All of the mentioned Answer: a 15. Point out the correct statement: a) Mobile Web services are those in which information is transferred between applications and services over an Internet connection b) The mobile Web is fractured into many different competing operating systems and proprietary hardware C) The lack of expandable storage on mobile devices is a classic example of vendor lock- in d) All of the mentioned Answer: d 16. Which of the following mechanism is suited for content compatibility on the mobile Web ? a) content negotiation b) content description c) content attribute d) none of the mentioned Answer: a 17. Which of the following group aimed at promoting standards on mobile networks ? a) OMTP b) OTP c) MTP d) None of the mentioned Answer: a 18. Which of the following vendors were part of WAC promote the market for mobile applications ? a) Motorola

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b) Nokia c) Sony Ericsson d) All of the mentioned Answer: d 19. Which of the following framework is used for creating mobile interfaces and subsystems by OMTP ? a) XACML b) XLST c) XAM d) None of the mentioned Answer: a 20. Which of the following standard mobile API is based on a set of JavaScript APIs ? a) CDMA API b) GSMA OneAPI c) DesAPI d) All of the mentioned Answer: b

10.12 ASSIGNMENT QUESTION BANK PART A (SHORT ANSWER QUESTIONS)

Blooms Course S. No Questions Taxonomy Outcome Level UNIT –I 1. DefineComputer Network Knowledge A

2. Define Distributed Computing Knowledge A

3. Explain the Client Server architecture Comprehension B

4. Analyze Parallel programming Analysis D

5. Explain Data Integrity Comprehension B Knowledge 6. What is Peer to Peer Network A Knowledge 7. What is Grid Computing. A

8. Define cloud Knowledge A

9. Explain Fault Tolerance. Evaluation E

10. Define Performance. Knowledge A

11. Define Cluster. Knowledge A

12. What is Distributed operating system Knowledge A

13. Define Scalability. Knowledge A

14. Explain Distributed Programming. Comprehension B

15. Which platforms are used for large scale cloud computing? Knowledge A

UNIT –II

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1. Classify different layers in cloud computing Analysis D

2. Define IaaS. Knowledge A

3. Define SaaS Knowledge A

4. Define PaaS. Knowledge A

5. Define Virtualization. Knowledge A

6. ExplainMash up of cloud Services Evaluation E

7. What is Data Center Knowledge A

8. Demonstrate cloning of VM Comprehension B

9. List the major design goals of cloud computing. Analysis D

10. Define Cloud Watermarking? Knowledge A

UNIT -III

1. Definemetadata Knowledge A

2. Define Granularity Knowledge B

3. Classifyregistries Analysis B

4. Explain about AMGA Comprehension B

5. Define Semantic web Knowledge A

6. Explain about workflow specification Evaluation E

UNIT –IV

1 DefineCluster management Knowledge A

2 DefineMapReduce. Knowledge A

3 Define machine learning. Knowledge A

4 Explain about Aneka Comprehension B

5 Explain about Microsoft Azure Comprehension B

6 Explain about Data Partitioning Comprehension B

7 Define Mapping Knowledge A

8 DefineCluster management Knowledge A

UNIT –V

1 Define Grid Knowledge A

2 DefineCPU scavenging Knowledge A

3 Explain Grid Resource Aggregation. Comprehension B

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4 Explain about Data Replication Comprehension B

5 Explain Data distribution in EDG Evaluation E

6 DefineBroker Knowledge A

7 Explain Globus Job workflow Comprehension B

8 DefineResource management? Knowledge A

9 Explain virtual organization Comprehension B

PART B (LONG ANSWER QUESTIONS)

Blooms S. Course Question Taxonomy No Outcome Level

UNIT –I

1. Compare Elasticity and Scalability Comprehension B

2. List the different types of users of cloud Knowledge A

3. What are the benefits of cloud computing Knowledge A

4. Explain about platform Evolution Comprehension B

5. What are the design objectives of Distributed computing Knowledge A

6. Explain the design issues of a cluster Comprehension B

7 Compare Amoeba and DCE Comprehension B

8 ExplainOGSA? Comprehension B

9 Compare unstructured and structured overlay networks Comprehension B

Comprehension, 10 ExplainInternet Cloud E Evaluation

UNIT –II

1. What are the different data types used in cloud computing Knowledge A

2. What are the different models for deployment in cloud computing Knowledge A

3. Comparecloud computing and mobile computing Comprehension B

4. What are the advantages of cloud services Knowledge A

5. Demonstrateinterconnection of Modular Data centers. Comprehension B

6. What are different issues in managing data centers Comprehension B

7 What are different techniques to manage Data and Software Comprehension B

8 Explainabout different strategies for Cloud security defense Knowledge A

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9 Explainabout Distributed Intrusion Comprehension B

UNIT –III

1. ExplainOGSA architecture Comprehension B

2. Compare Selected Messaging and Queuing Systems. Comprehension B

3 Demonstrateapplications of Grid middleware Comprehension B

4 What are different categories of information of Registries Knowledge A

5 Explain semantic grid architecture Comprehension B

6 Explain UDDI and Service registries Comprehension B

UNIT –IV

1. Explain about Google File System Comprehension B

2. Illustrate Hadoop Distributed File System Comprehension B

3. Explain about Dryad and DryadLINQ from Microsoft Comprehension B

4. ExplainTablet location hierarchy in using the BigTable Comprehension B

5. Explainabout Amazon Elastic Block Store(EBS) Comprehension B

6. Illustrate about Virtual Appliances? Comprehension B

UNIT – V

1 Explain about different Grid data access models. Comprehension B

2 Explain about EDG architecture? Evaluation E

3 Explain about Fuzzy Trust model? Comprehension B

4 Explain about Adaptive prediction scheme. Comprehension B

5 What is Technology Fusion Knowledge A

PART C (CRITICAL THINKING QUESTIONS) Blooms Course S. No Question Taxonomy Outcome Level UNIT –I

1 Take a sample data and solve scaling problem using Gustafson’s law Analysis D Compare the energy efficiency at different layers in Distributed 2 Comprehension B computing 3 Explain the different models of Parallel and Distributed programming Comprehension B

UNIT –II

1 List the challenges in Architectural Design Knowledge A

2 Explain different services provided by Amazon AWS Comprehension B

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3 Explain Inter-Cloud resource management Comprehension B

UNIT –III

1 Explain oracle publish subscribe model Comprehension B

2 ExplainGrid of grid services Evaluation E

3 Explain workflow Execution Engine Comprehension B

UNIT –IV

1 Explain about Aneka architecture Comprehension B

2 Explainthe Execution environment of Amazon S3. Comprehension B

3 Explain the workflow to create VM Comprehension B

UNIT –V

1 Explain about Grid resource monitoring with CGSP Comprehension B

2 Explain about Grid workload and Performance prediction Comprehension B

3 Explain about different trust models for Grid security enforcement. Comprehension B

4 Explain about Grid security Infrastructure Comprehension B

10.13 TUTORIALS QUESTION BANK GROUP - A (SHORT ANSWER QUESTIONS)

Blooms Course Taxonomy S. No Questions Outcome Level

UNIT –I 1. Define Utility Computing Knowledge A

2. Compare multi core CPU and many core CPU architectures. Comprehension D 3. Define Hardware virtualization Knowledge A 4. Compare Cloud and Grid Comprehension D 5. Explain the Evolution of SOA Comprehension D 6. Explain Virtual Networking Comprehension D 7. Explain about Multithreading technology Comprehension D 8. Definevirtual cluster Knowledge A 9. Explain about Amdahl’s law. Comprehension D 10. Explain how GPUs work Comprehension D 11. DefineHigh throughput computing Knowledge A 12. Define Virtual Infrastructure Knowledge A 13. Define Transparency in Programming Environments Knowledge A UNIT –II 1. Define Public cloud Knowledge A

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2 DefinePrivate Cloud Knowledge A 3 Define Hybrid cloud Knowledge A 4 Explain Cloud Ecosystems. Comprehension D

5 Explain about Google App engine for PaaS Application Knowledge A 6 Differentiate Distributed and Centralized computing Analysis E 7 Define Map Reduce. Knowledge A UNIT –III 1. DefineQueuing Knowledge A 2. DefineContent Tagging Knowledge A 3. Explain about wikis Comprehension B 4. Explain about Blogs Comprehension B 5. Define Packaging Knowledge A 6. Explain about UDDI Comprehension B UNIT –IV 1 DefineData Affinity Knowledge A 2 Explain DPFS Comprehension B 3 Explain about Worker and webroles Comprehension C 4 Define Combiner function Knowledge A 5 Define Computation Partitioning Knowledge A 6 Define Map function Knowledge B 7 Define Partitioning function. Knowledge C UNIT –V 1 Explain about OGSA interfaces Comprehension B 2 Define Virtual Organization. Knowledge A 3 Define striped Data transfers Knowledge A 4 DefineGrid service migration Knowledge A 5 DefineParallel Data transfer. Knowledge A 6 Explaindata distribution in EDG Comprehension B 7 List applications of china grid Knowledge A 8 Define Resource brokering Knowledge A

GROUP - II (LONG ANSWER QUESTIONS) Blooms Course S. No Questions Taxonomy Outcome Level UNIT –I

1 What are the challenges in P2P computing . Knowledge A

2 List the various dimensions of scalability Knowledge A

3 Explain different threats to Systems and Networks Comprehension D

4 Compare Scalability and OS image Count. Comprehension D

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5 Explain GPU Programming model Comprehension D

6 Explain about System area Interconnects Comprehension D

7 Explain VM primitive operations Knowledge A

8 Discuss about Grid families Knowledge A

UNIT –II

1 Explain about Warehouse scale and Data center design Knowledge A Comprehension, 2 Explain in detail about Inter-Module connection Network Synthesis, B Evaluation 3 Discuss the enabling techniques for clouds Comprehension C

4 Define HDFS and explain its block size and replication factor Knowledge D Application, 5 Write a note on generic cloud architecture E Synthesis Comprehension, 6 Explain about surge of private clouds Synthesis, E Evaluation UNIT –III

1 DescribePublish-Subscribe Model and Notification Knowledge A Comprehension, 2 Describe Enterprise Multitier Architecture B Evaluation 3 Describe briefly about Workflow standards. Comprehension C

4 Explain about Metadata Catalogs. Comprehension B

5 Discuss scripting workflow system swift Knowledge E

6 Discuss semantic grid-related concepts and technologies Comprehension E Comprehension, 7 Explain about Job execution environments and monitoring Synthesis, A Evaluation UNIT –IV Knowledge, 1 DescribeParallel computing and Programming paradigms Comprehension, A Evaluation Knowledge, 2 Describe MapReduce framework Comprehension, B Evaluation Knowledge, 3 Describe architecture of MapReduce in Hadoop Comprehension, C Evaluation Comprehension, 4 Explain about Metadata Catalogs. Synthesis, D Evaluation Knowledge, 5 Describe about the Google App Engine Comprehension, E Evaluation UNIT –V

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Application, 1 Write about Globus Toolkit Architecture. A Synthesis Application, 2 Write Chinagrid Support platform B Synthesis Application, 3 Write about data grid in European Union C Synthesis 4 List Grid application trends Knowledge D Comprehension, 5 Explain about Producer/Consumer model for grid monitoring Synthesis, E Evaluation

PART C (CRITICAL THINKING QUESTIONS)

Blooms Course S. No Question Taxonomy Outcome Level UNIT –I

1 Discuss Layered Architecture for Web Service and Grids Knowledge A Explain about Parallel and Distributed programming models and Comprehension, 2 B Tool Sets Synthesis Application, 3 Explain Energy efficiency in Distributed computing C Synthesis UNIT –II

1 List different public clouds and discuss them in detail Knowledge A

2 Explain in detail about Microsoft Windows Azure Comprehension B

3 Explain about Interconnection of Modular Data Centers Comprehension B

UNIT –III

1 Explain REST architectural elements Comprehension B

2 Explain Services and standards used in CICC Comprehension B

3 Discuss the HUBzero architecture Comprehension E

UNIT –IV

1 Discuss MapReduce Actual data and control flow Comprehension B

2 Explain about Hadoop library from Apache Comprehension B

3 Sketch the process of Running a job in Hadoop Understand E

UNIT -V Application, 1 Write about Dynamic formation of Virtual Organizations A Synthesis 2 Explain about Grid standards and API Knowledge B

3 Explain about Globus container Understand D

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11. DATA MINING AND DATA WAREHOUSING(A10541)

11.0 COURSE DESCRIPTION

Course Title DATA MINING AND DATA WAREHOUSING Course Code A10541 Regulation MLR15 Lectures Tutorials Practical Credits Course Structure 3 1 3 3 Course Coordinator Mrs. ChaitraliDangare Team of Instructors Mr. Venkat Shiva Mr. Srinivas Reddy Ms. Pushpa Priyanka

11.1 COURSE OVERVIEW:

This course helps the students to understand the overall architecture of a data warehouse and methods for data gathering and data pre-processing using OLAP tools. The different data mining models and techniques will be discussed in this course. Data mining and data warehousing applications in bioinformatics will also be explored.

11.2 PREREQUISITE(S):

Level Credits Periods/Weeks Prerequisites UG 3 4 Database Management Systems, Probability & Statistics

11.3 MARKS DISTRIBUTION:

a) Marks Distributions (Traditional Evaluation methods)

University End Session Marks (25 Marks) Total Marks Exam Marks There shall be 2 midterm examinations. Each midterm examination consists of subjective type and objective type tests. The subjective test is for 10 marks, with duration of 1 hour. Subjective test of each semester shall contain 4 questions; the student has to answer 2 questions, each carrying 5 marks. The objective type test is for 10 marks with duration of 20 minutes. It consists of 10 multiple choice and 10 objective type 75 100 questions, the student have to answer all the questions and each carry half mark. First midterm examination shall be conducted for the first two and half units of syllabusand second midterm examination shall be conducted for the remaining portion. Five marks are embarked for assignments. There shall be two assignments in every theory course. Marks shall be awarded considering the average of two assignments in each course

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b) Course Outcomes and Methods for Assessing

Sl. No. Course Outcomes Assessment Methods A. Design a data mart or data warehouse for any Assignment/ Case study organization B. Develop skills to write queries using DMQL Assignment/ Quiz C. Extract knowledge using data mining techniques Assignment/ Examination D. Adapt to new data mining tools. Assignment/ Examination E. Explore recent trends in data mining such as web Assignment/ mining, spatial-temporal mining Examination

11.4 EVALUATION SCHEME:

S. No Component Duration Marks 1 I Mid Examination 80 minutes 20 2 I Assignment -- 5 3 II Mid Examination 80 minutes 20 4 II Assignment -- 5 5 External Examination 3 hours 75

11.5 COURSE OBJECTIVES : I. To teach the basic principles, concepts and applications of data warehousing and data mining. II. To introduce the task of data mining as an important phase of knowledge recovery process. III. To familiarize Conceptual, Logical, and Physical design of Data Warehouses OLAP applications and OLAP deployment. IV. To impart knowledge of the fundamental concepts that provide the foundation of data mining.

11.5 COURSE OUTCOMES:

Sr. No. Course Outcomes Blooms Level

1. Design a data mart or data warehouse for any organization BL1, BL3,BL6

2. Develop skills to write queries using DMQL BL3, BL6

3. Extract knowledge using data mining techniques BL2, BL3, BL4

4. Adapt to new data mining tools. BL2, BL6 Explore recent trends in data mining such as web mining, spatial- 5. BL4,BL6 temporal mining

BLOOMS LEVEL (BL) BL 1: Remember / knowledge BL2: Understanding BL3: Apply BL 4: Analyze BL 5: Evaluate BL 6: Create MLR Institute of Technology, Dundigal, Hyd-500043 Page 63

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11.6 HOW PROGRAM OUTCOMES ARE ASSESSED:

Program Outcomes Level Proficiency assessed by An ability to apply the knowledge of mathematics, computing, science and engineering PO1 S Assignments, Exercises to solve the computer science and engineering problems An ability to design and conduct engineering PO2 experiments ,as well as to analyze and interpret S Exercises data An ability to design and construct hardware and PO3 software system, component, or process to meet S Exercises desired needs, within realistic constraints. Demonstrate an ability to visualize and work on PO4 laboratory and multi-disciplinary tasks S Exercises individually or as a member within the teams An ability to demonstrate skills to use the techniques, modern engineering Tools, Software PO5 H Exercises and equipments necessary to analyze computer engineering Problems. An understanding of professional, social and PO6 N -- ethical responsibility An ability to recognize the global issues like green initiatives and alternate energy sources and PO7 N -- to take technology to villages and to recognize the rural requirements The broad education necessary to understand the PO8 impact of engineering solutions in a global, S Seminars, Discussions economic, environmental, and societal context. Graduate will develop confidence for self education and acquire new knowledge in the PO9 computing discipline and ability and practice for H Exercises Multi-disciplinary tasks as a member within the teams To communicate effectively Seminars, Power point PO10 S presentations An ability to use the techniques, skills and PO11 modern engineering tools necessary for H Exercises Engineering practice. Graduates are able to participate and succeed in PO12 competitive examination like GATE, GRE, S Exams, Discussions TOEFEL,GMAT PO13 An ability to setup an enterprise N -- The use of current application software and the design and use of operating systems and analysis PO14 designing and testing ,documentation of computer S Exercises programs for the use in computer science and engineering technologies

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N = None S = Supportive H = Highly Related 11.7 SYLLABUS:

UNIT - I Introduction To Data Mining: Motivation, Importance, Definition of Data Mining, Kind of Data,Data Mining Functionalities, Kinds of Patterns, Classification of Data Mining Systems, Data MiningTask Primitives, Integration of A Data Mining System With A Database or Data Warehouse System,Major Issues In Data Mining, Types of Data Sets and Attribute Values, Basic Statistical Descriptionsof Data, Data Visualization, Measuring Data Similarity. Preprocessing:Data Quality, Major Tasks in Data Preprocessing, Data Reduction, DataTransformation and Data Discretization, Data Cleaning and Data Integration.

UNIT - II Data Warehousing And On-Line Analytical Processing: Data Warehouse basicconcepts, Data Warehouse Modeling - Data Cube and OLAP, Data Warehouse Design and Usage,Data Warehouse Implementation, Data Generalization by Attribute-Oriented Induction. Data Cube Technology: Efficient Methods for Data Cube Computation, Exploration andDiscovery in Multidimensional Databases.

UNIT - III Mining Frequent Patterns, AssociationsAnd Correlations: Basic Concepts,Efficient and Scalable Frequent Item set Mining Methods, Are All the Pattern Interesting, PatternEvaluation Methods, Applications of frequent pattern and associations. Frequent Pattern And Association Mining:A Road Map, Mining Various Kinds ofAssociation Rules, Constraint-Based Frequent Pattern Mining, Extended Applications of FrequentPatterns.

UNIT - IV Classification: Basic Concepts, Decision Tree Induction, Bayesian Classification Methods, RuleBasedClassification, Model Evaluation and Selection, Techniques to Improve ClassificationAccuracy: Ensemble Methods, Handling Different Kinds of Cases in Classification, Bayesian BeliefNetworks, Classification by Neural Networks, Support Vector Machines, Pattern-Based Classification,Lazy Learners (or Learning from Your Neighbors), Other Classification Methods.

UNIT - V Cluster Analysis: Basic Concepts of Cluster Analysis, Clustering structures, Major Clustering Approaches, Partitioning Methods, Hierarchical Methods, Density-Based Methods, Model- Based Clustering - The Expectation-Maximization Method, Other Clustering Techniques, Clustering HighDimensional Data, Constraint-Based and User-Guided Cluster Analysis, Link-Based Cluster Analysis, Semi-Supervised Clustering and Classification, Bi-Clustering, Collaborative Clustering. Outlier Analysis:Why outlier analysis, Identifying and handling of outliers, Distribution- Based Outlier Detection: A Statistics-Based Approach, Classification-Based Outlier Detection, Clustering Based Outlier Detection, Deviation-Based Outlier Detection, Isolation- Based Method: From Isolation Tree to Isolation Forest.

TEXT BOOKS: 1. Jiawei Han, Micheline Kamber, Jian Pei (2012), Data Mining: Concepts and Techniques, 2nd edition, Elsevier, United States of America.

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2. Jiawei Han, Micheline Kamber, Jian Pei (2012), Data Mining: Concepts and Techniques, 3rdedition, Elsevier, United States of America.

REFERENCE BOOKS: 1. Margaret H Dunham (2006), Data Mining Introductory and Advanced Topics, 2nd edition,Pearson Education, New Delhi, India. 2. Amitesh Sinha (2007), Data Warehousing, Thomson Learning, India. 3. Xingdong Wu, Vipin Kumar (2009), the Top Ten Algorithms in Data Mining, CRC Press, UK.

11.8 COURSE PLAN:

Lecture Blooms Topics to be covered Course Learning Outcomes Reference No. Level Introduction To Data Mining: Motivation, Outline the importance of data 1-2 T1-1.1 BL2, BL4 Importance mining in big data technology.

3-4 Definition of Data Mining, Kind of Data Define data mining T1-1.2,1.3 BL1

List out advantages of data 5-6 Data Mining Functionalities, Kinds of Patterns T1-1.4 BL1 mining

7 Classification of Data Mining Systems Classify data mining T1-1.6 BL2

Data Mining Task Primitives, Integration of A Distinguish data warehouse from 8-9 Data Mining System With A Database or Data T1-1.7,1.8 BL1,BL3 other databases Warehouse System . Major Issues In Data Mining, Types of Data Discuss and List out data set 10-11 T1-1.9 BL1 Sets and Attribute Values types and values DescribeStatistical Descriptions 12 Basic Statistical Descriptions of Data T2-2.2 BL2 of Data

13-14 Data Visualization, Measuring Data Similarity Show data visualization T2-2.3,2.4 BL3

Preprocessing: Data Quality, Major Tasks in 15-16 Discuss Data preprocessing steps T2-3.1,3.4 BL2 Data Preprocessing, Data Reduction Data Transformation and Data Discretization, Define data preprocessing 17-19 T2-3.5 BL1 Data Cleaning and Data Integration process Data Warehousing And On-Line Analytical 20 Describe Data Warehousing T2-4.1 BL1 Processing: Data Warehouse basic concepts Data Warehouse Modeling - Data Cube and Implementation of Data 21-23 OLAP, Data Warehouse Design and Usage, T2-4.2 BL3 warehouse Data Warehouse Implementation Data Generalization by Attribute-Oriented 24 Understand Data Generalization T2-4.5 BL2 Induction Data Cube Technology: Efficient Methods for 25-26 Data Cube Computation, Exploration and Express Data cube technology T1-4.1 BL6 Discovery in Multidimensional Databases Mining Frequent Patterns, Associations And Define association and 27-28 Correlations: Basic Concepts, Efficient and T1-5.1,5.2 BL1 correlations Scalable Frequent Item set Mining Methods Are All the Pattern Interesting, Pattern Illustrate Pattern Evaluation 29-31 Evaluation Methods, Applications of frequent T2-6.3 BL2 Methods pattern and associations MLR Institute of Technology, Dundigal, Hyd-500043 Page 66

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Frequent Pattern And Association Mining: A 32 Describe RoadMap T1-5.1 BL2 Road Map

33 Mining Various Kinds of Association Rules Discuss Association Rules T1-5.3 BL2

Constraint-Based Frequent Pattern Mining, 34-35 Explain Frequent Pattern T1-5.5 BL2 Extended Applications of Frequent Patterns Classification: Basic Concepts, Decision Tree 36 Define Classification T2-8.1,8.2 BL1 Induction Bayesian Classification Methods, Rule Based 37-39 Express Classification methods T2-8.3,8.4 BL6 Classification, Model Evaluation and Selection Techniques to Improve Classification Apply different methods on 40-41 Accuracy: Ensemble Methods, Handling T2-8.6 BL3 classification Different Kinds of Cases in Classification Bayesian Belief Networks, Classification by 42-43 Illustrate neural networks T2-9.1 BL2 Neural Networks

44 Support Vector Machines Define Support Vector Machines T2-9.3 BL1

Pattern-Based Classification, Lazy Learners (or Show different classification T2- 45-47 Learning from Your Neighbors), Other BL3 methods 9.4,9.5,9.6 Classification Methods Cluster Analysis: Basic Concepts of Cluster 48 Explain clustering T2-10.1 BL2 Analysis, Clustering structures Major Clustering Approaches, Partitioning Methods , Hierarchical Methods, Density- T2- 49-53 Based Methods, Model-Based Clustering - The Discuss ClusteringMethods 10.2,10.3,10. BL2 Expectation-Maximization Method, Other 4,10.5,10.6 Clustering Techniques

54 Clustering High Dimensional Data Apply Clustering T2-11.2 BL3

Constraint-Based and User-Guided Cluster 55-56 Analysis, Link-Based Cluster Analysis, Semi- Distinguish Clustering Methods T1-7.10 BL4 Supervised Clustering Classification, Bi-Clustering, Collaborative 57-58 Define Classification T2-11.2.3 BL1 Clustering Outlier Analysis: Why outlier analysis, 59 Describe outer analysis T2-12.1 BL1 Identifying and handling of outliers Distribution-Based Outlier Detection: A 60-61 Explain Statistics-Based method T1-7.11 BL2 Statistics-Based Approach Classification-Based Outlier Detection, Apply outlier detection methods 62-63 Clustering Based Outlier Detection, Deviation- T1-7.11 BL3 on data Based Outlier Detection Isolation-Based Method: From Isolation 64 Tree Illustrate IsolationTree T1-7.11 BL2 to Isolation Forest

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11.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OFPROGRAM OUTCOMES Course Outcomes Course Objective a b c d e I S II S H III S H IV S S S S=Supportive H=Highly Related 11.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF

PROGRAM OUTCOMES

Program Outcomes Course Outcomes A B C D E F G H I J k L M N A H S S S H S S B S S S S C S S S S D H H S E S S S=Supportive H=Highly Related

11.11 OBJECTIVE BITS

UNIT I

1. Data mining is a. The actual discovery phase of a knowledge discovery process b. The stage of selecting the right data for a KDD process c. Subject-oriented integrated time variant non-volatile collection of data in support of management d. None of these Answer: A 2. Classification task referred to a. A subdivision of a set of examples into a number of classes b. A measure of the accuracy, of the classification of a concept that is given by a certain theory c. The task of assigning a classification to a set of examples d. None of these Answer: C

3. Multi-dimensional knowledge is a. A class of learning algorithms that try to derive a Prolog program from examples b. A table with n independent attributes can be seen as an n-dimensional space c. A prediction made using an extremely simple method, such as always predicting the same output.

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d. None of these Answer: B 4. Prediction is a. The result of the application of a theory or a rule in a specific case b. One of several possible enters within a database table that is chosen by the designer as the primary means of accessing the data in the table. c. Discipline in statistics that studies ways to find the most interesting projections of multi-dimensional spaces. d. None of these Answer: A 5. Binary attribute are a. This takes only two values. In general, these values will be 0 and 1 and .they can be coded as one bit b. The natural environment of a certain species c. Systems that can be used without knowledge of internal operations d. None of these Answer: A 6. Euclidean distance measure is a. A stage of the KDD process in which new data is added to the existing selection. b. The process of finding a solution for a problem simply by enumerating all possible solutions according to some pre-defined order and then testing them c. The distance between two points as calculated using the Pythagoras theorem d. None of these Answer: C 7. Query tool is meant for ______. a. Data Acquisition. b. Information Delivery. c. Information Exchange. d. Communication Answer: A 8. Dimensionality reduction reduces the data set size by removing ______a. Relevant attributes. b. Irrelevant attributes. c. Derived attributes. d. Composite attributes. Answer: B 9. ______is a method of incremental conceptual clustering. a. CORBA. b. OLAP. c. COBWEB. d. STING. Answer: C 10. Effect of one attribute value on a given class is independent of values of other attribute is called______. a. Value independence. b. Class conditional independence. c. Conditional independence. d. Unconditional independence Answer: A

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11. MDDB stands for ______. a. A. multiple data doubling. b. B. multidimensional databases. c. C. multiple double dimension. d. D. multi-dimension doubling. Answer: B 12. ______is data about data. a. Metadata. b. Microdata c. Minidata. d. Multidata. Answer: A 13. The term that is not associated with data cleaning process is ______. a. Domain consistency. b. Deduplication. c. Disambiguation. d. Segmentation Answer: D 14. The first International conference on KDD was held in the year ______. a. 1996. b. 1997 c. 1995. d. 1994. Answer: C 15. Removing duplicate records is a process called ______. a. Recovery. b. Data Cleaning. c. Data Cleansing. d. Data Pruning. Answer: B 16. Which of the following is a predictive model? a. Clustering. b. Regression. c. Summarization. d. Association rules. Answer: B 17. A ______model identifies patterns or relationships. a. Descriptive. b. Predictive. c. Regression. d. Time series analysis. Answer: A 18. In ______, the value of an attribute is examined as it varies over time. a. Regression. b. Time series analysis. c. Sequence discovery. d. Prediction Answer: B 19. Treating incorrect or missing data is called as ______. a. Selection.

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b. Preprocessing. c. Transformation. d. Interpretation Answer: B 20. ______are needed to identify training data and desired results. a. Programmers. b. Designers. c. Users. d. Administrators

UNIT II

1. ______is a subject-oriented, integrated, time-variant, nonvolatile collection of data in support of management decisions. A. Data Mining. B. Data Warehousing. C. Web Mining. D. Text Mining. Answer: B 2. The data is stored, retrieved & updated in ______. A. OLAP. B. OLTP. C. SMTP D. FTP. Answer: B 3. ______is the heart of the warehouse. A. Data mining database servers. B. Data warehouse database servers. C. Data mart database servers. D. Relational data base servers Answer: B 4. ______is the specialized data warehouse database. A. Oracle. B. DBZ. C. Informix. D. Redbrick. Answer: D 5. ______defines the structure of the data held in operational databases and used byoperational applications. A. User level metadata. B. Data warehouse metadata. C. Operational metadata. D. Data mining metadata. Answer: C 6. ______is held in the catalog of the warehouse database system. A. Application level metadata. B. Algorithmic level metadata. C. Departmental level metadata. D. Core warehouse metadata. Answer: B

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7. The star schema is composed of ______fact table. A. one. B. two. C. three. D. Four Answer: A 8. The source of all data warehouse data is the______. A. operational environment. B. informal environment. C. formal environment. D. technology environment. Answer: A 9. Data warehouse contains______data that is never found in the operational environment. A. Normalized. B. Informational. C. Summary. D. Denormalized. Answer: C 10. Data redundancy between the environments results in less than ______percent. A. one. B. two. C. three. D. four. Answer: A 11. ______is a good alternative to the star schema. A. Star schema. B. Snowflake schema. C. Fact constellation. D. Star-snowflake schema. Answer: C 12. The active data warehouse architecture includes ______A. at least one data mart. B. data that can extracted from numerous internal and external sources. C. near real-time updates. D. all of the above Answer: D 13. Fact tables are ______. A. completely demoralized. B. partially demoralized. C. completely normalized. D. partially normalized Answer: C 14. ______are some popular OLAP tools. A. Metacube, Informix. B. Oracle Express, Essbase. C. HOLAP. D. MOLAP Answer: A

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15. Which of the following is not a component of a data warehouse? A. Metadata. B. Current detail data. C. Lightly summarized data D. Component Key. Answer: D 16. The data Warehouse is______. A. read only B. write only. C. read write only. D. none. Answer: A 17. Expansion for DSS in DW is______. A. Decision Support system B. Decision Single System. C. Data Storable System. D. Data Support System. Answer: A 18. The important aspect of the data warehouse environment is that data found within the data warehouse is______. A. subject-oriented. B. time-variant C. integrated. D. All of the above. Answer: D 19. The time horizon in Data warehouse is usually ______. A. 1-2 years. B. 3-4years. C. 5-6 years. D. 5-10 years. Answer: D 20. Data can be updated in _____environment. A. data warehouse. B. data mining. C. operational D. informational. Answer: C UNIT – III 1. This specifies the data mining functions to be performed A. task-relevant data B. type of knowledge to be mined C. background knowledge D. none ANS: B 2. What do you mean by support(A)? a. Total number of transactions containing A b. Total Number of transactions not containing A c. Number of transactions containing A / Total number of transaction s d. Number of transactions not containing A / Total number of transactions Ans: c

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3. How do you calculate Confidence(A -> B)? a. Support(A B) / Support (A) b. Support(A B) / Support (B) c. Support(A B) / Support (A) d. Support(A B) / Support (B) Ans: a 4. Which of the following is direct application of frequent item set mining? a. Social Network Analysis b. Market Basket Analysis c. Outlier Detection d. Intrusion Detection Ans: b 5. When do you consider an association rule interesting? a. If it only satisfies min_support b. If it only satisfies min_confidence c. If it satisfies both min_support and min_confidence d. There are other measures to check so Ans: c 6. What is the relation between candidate and frequent itemsets? a. A candidate itemset is always a frequent itemset b. A frequent itemset must be a candidate itemset c. No relation between the two d. Both are same Ans: b 7. Which of the following is true? a. Both apriori and FP-Growth uses horizontal data format b. Both apriori and FP-Growth uses vertical data format c. Apriori uses horizontal and FP-Growth uses vertical data format d. Apriori uses vertical and FP-Growth uses horizontal data format Ans: a 8. What will happen if support is reduced? a. Number of frequent itemsets remains same b. Some itemsets will add to the current set of frequent itemsets c. Some itemsets will become infrequent while others will become frequent d. Can not say Ans: b 9. What is frequent pattern growth? a. Same as frequent itemset mining b. Use of hashing to make discovery of frequent itemsets more efficient c. Mining of frequent itemsets without candidate generation d. None of the above Ans: c 10. The apriori algorithm works in a ..and ..fashion? a. top-down and depth-first b. top-down and breath-first c. bottom-up and depth-first d. bottom-up and breath-first Ans: d 11. When is sub-itemset pruning done? a. A frequent itemset 'P' is a proper subset of another frequent itemset 'Q'

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b. Support (P) = Support(Q) c. When both a and b is true d. When a is true and b is not Ans: c 12. What is the difference between absolute and relative support? a. Absolute - Minimum support count threshold and Relative - Minimum support threshold b. Absolute - Minimum support threshold and Relative - Minimum support count threshold c. Both mean same d. none of these Ans: a 13. The second phaase of Apriori algorithm is ______. A. Candidate generation. B. Itemset generation C. Pruning. D. Partitioning Ans: c 14. Rule based classification algorithms generate ______rule to perform the classification. A. if-then. B. while. C. do while. D. switch. Ans: c 15. The left hand side of an association rule is called ______A. consequent. B. onset. C. antecedent D. precedent. ANSWER: C 16. The right hand side of an association rule is called _____. A. consequent. B. onset C. antecedent. D. precedent. ANSWER: A 17. All set of items whose support is greater than the user-specified minimum support are called as______. A. border set. B. frequent set. C. maximal frequent set. D. lattice. ANSWER: B 18. If a set is a frequent set and no superset of this set is a frequent set, then it is called ______. A. maximal frequent set. B. border set. C. lattice. D. infrequent sets.

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ANSWER: A 19. Any subset of a frequent set is a frequent set. This is ______. A. Upward closure property. B. Downward closure property. C. Maximal frequent set. D. Border set. ANSWER: B 20. Any superset of an infrequent set is an infrequent set. This is ______. A. Maximal frequent set. B. Border set. C. Upward closure property. D. Downward closure property. ANSWER: C

UNIT – IV 1. ______and prediction may be viewed as types of classification. A. Decision. B. Verification. C. Estimation. D. Illustration. ANSWER: C 2. ______can be thought of as classifying an attribute value into one of a set of possible classes. A. Estimation. B. Prediction. C. Identification. D. Clarification. ANSWER: B 3. Prediction can be viewed as forecasting a______value. A. non-continuous. B. constant. C. continuous. D. variable. ANSWER: C 4. ______data consists of sample input data as well as the classification assignment for the data. A. Missing. B. Measuring. C. Non-training. D. Training. ANSWER: D 5. Rule based classification algorithms generate ______rule to perform the classification. A. if-then. B. while. C. do while. D. switch. ANSWER: A 6. ______are a different paradigm for computing which draws its inspiration from neuroscience.

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A. Computer networks. B. Neural networks. C. Mobile networks D. Artificial networks. ANSWER: B 7. ______is the most widely applied neural network technique. A. ABC B. PLM. C. LMP. D. MLP. ANSWER: D 8. Classification method in which upper and lower limits of interval is also in class interval itself is called A. exclusive method B. inclusive method C. mid-point method D. ratio method ANSWER: B 9. Summary and presentation of data in tabular form with several non-overlapping classes is referred as A. nominal distribution B. ordinal distribution C. chronological distribution D. frequency distribution ANSWER: D 10. The classification method in which the upper limit of interval is same as of lower limit class interval is called A. exclusive method B. inclusive method C. mid-point method D. ratio method ANSWER: A 11. The method of sampling in which the population is divided in to mutual exclusive groups that have useful context in statistical research is classified as A. stratified sampling B. regular group sampling C. irregular group sampling D. direct group sampling ANSWER: A 12. The types of probability distributions by taking their functions of considerations must include A. posterior probability distribution B. discrete probability distribution C. continuous probability distribution D. both b and c ANSWER: D 13. The data table which is presented in tabular form on the basis of single characteristics is classified as

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A. simple table B. complex table C. percentage table D. interval table ANSWER: A 14. Where does the bayes rule can be used? a) Solving queries b) Increasing complexity c) Decreasing complexity d) Answering probabilistic query ANSWER: D 15. What does the bayesian network provides? a) Complete description of the domain b) Partial description of the domain c) Complete description of the problem d) None of the mentioned ANSWER: A 16. How the bayesian network can be used to answer any query? a) Full distribution b) Joint distribution c) Partial distribution d) All of the mentioned ANSWER: B 17. How many terms are required for building a bayes model? a) 1 b) 2 c) 3 d) 4 ANSWER: C 18. Which of the following is true for neural networks? (i) The training time depends on the size of the network. (ii) Neural networks can be simulated on a conventional computer. (iii) Artificial neurons are identical in operation to biological ones. a) All of the mentioned b) (ii) is true c) (i) and (ii) are true d) None of the mentioned ANSWER: C 19. Which is true for neural networks? a) It has set of nodes and connections b) Each node computes it’s weighted input c) Node could be in excited state or non-excited state d) All of the mentioned ANSWER: D 20. Neural Networks are complex ______with many parameters. a) Linear Functions b) Nonlinear Functions c) Discrete Functions d) Exponential Functions ANSWER: A MLR Institute of Technology, Dundigal, Hyd-500043 Page 78

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UNIT V 1. ______clustering technique start with as many clusters as there are records, with each cluster having only one record. A. Agglomerative. B. divisive. C. Partition. D. Numeric. Answer : A 2. ______clustering techniques starts with all records in one cluster and then try to split that cluster into small pieces. A. Agglomerative. B. Divisive. C. Partition. D. Numeric. ANSWER: B 3. Which of the following is a data set in the popular UCI machine-learning repository? A. CLARA B. CACTUS. C. STIRR. D. MUSHROOM. ANSWER: D 4. In ______algorithm each cluster is represented by the center of gravity of the cluster A. k-medoid. B. k-means. C. STIRR. D. ROCK. ANSWER: B 5. In ______each cluster is represented by one of the objects of the cluster located near the center. A. k-medoid. B. k-means. C. STIRR. D. ROCK. ANSWER: A 6. Pick out a k-medoid algoithm. A. DBSCAN. B. BIRCH. C. PAM. D. CURE. ANSWER: C 7. Pick out a hierarchical clustering algorithm. A. DBSCAN B. BIRCH. C. PAM. D. CURE. ANSWER: A 8. CLARANS stands for ______.

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A. CLARA Net Server. B. Clustering Large Application RAnge Network Search. C. Clustering Large Applications based on RANdomized Search. D. Clustering Application Randomized Search. ANSWER: C 9. The basic partition algorithm reduces the number of database scans to ______& divides it into partitions. A. one. B. two C. three. D. four. ANSWER: B 10. Point out the correct statement: A. The choice of an appropriate metric will influence the shape of the clusters B. Hierarchical clustering is also called HCA C. In general, the merges and splits are determined in a greedy manner D. All of the Mentioned ANSWER: D 11. Which of the following is finally produced by Hierarchical Clustering ? A. final estimate of cluster centroids B. tree showing how close things are to each other C. assignment of each point to clusters D. all of the Mentioned ANSWER: B 12. Which of the following is required by K-means clustering ? A. defined distance metric B. number of clusters C. initial guess as to cluster centroids D. all of the Mentioned ANSWER: D 13. Point out the wrong statement: a) k-means clustering is a method of vector quantization b) k-means clustering aims to partition n observations into k clusters c) k-nearest neighbor is same as k-means d) None of the Mentioned ANSWER: C 14. Which of the following function is used for k-means clustering ? a) k-means b) k-mean c) heatmap d) None of the Mentioned ANSWER: A 15. Which of the following clustering requires merging approach ? a) Partitional b) Hierarchical c) Naive Bayes d) None of the Mentioned ANSWER: B 16. Which of the following combination is incorrect ? a) Continuous – euclidean distance

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Department of CSE b) Continuous – correlation similarity c) Binary – manhattan distance d) None of the Mentioned ANSWER: D 17. What is the minimum no. of variables/ features required to perform clustering? A. 0 B. 1 C. 2 D. 3 ANSWER: B 18. Is it possible that Assignment of observations to clusters does not change between successive iterations in K-Means A. Yes B. No C. Can’t say D. None of these ANSWER: A 19. Which of the following clustering algorithms suffers from the problem of convergence at local optima? A. K- Means clustering algorithm B. Agglomerative clustering algorithm C. Expectation-Maximization clustering algorithm D. Diverse clustering algorithm ANSWER: D 20. In which of the following cases will K-Means clustering fail to give good results? A. Data points with outliers B. Data points with different densities C. Data points with round shapes D. . None of these E. ANSWER: D

11.12 TUTORIALQUESTIONS PART-A (SHORT ANSWER QUESTIONS)

Blooms S. Course Questions Taxonomy No Outcome Level UNIT-I 1. State the goals of data mining? Understand 3 2. Describe briefly about interesting pattern? Knowledge 1,3 3. List the steps involved in data pre-processing? Understand 1 4. Describe about the necessity of association rules? Knowledge 3 5. List some applications of data mining? Understand 1 UNIT II 1. Explain the definition of data warehouse? Understand 1 2. Distinguish between data mining and data warehouse? Understand 1 3. Identify any three functionality of data mining? Knowledge 4 List out the steps in the process of knowledge 4. Knowledge 3 discovery?

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5. Discuss relational databases? Understand 3 UNIT III 1. Name the steps in association rule mining? Understand 3 2. State how can we mine closed frequent itemsets? Understand 3 3. Define Support and Confidence? Knowledge 1 4. List the techniques of efficiency of Apriori algorithm? Understand 1 5. State maximal frequent itemset? Understand 1 UNIT IV Differentiate supervised learning and unsupervised Understand 1. 3 learning? 2. Name the steps in data classification? Understand 2 3. Define the decision tree? Understand 1 4. Explain the IF-THEN rules for classification? Understand 2 5. List the Attribute Selection Measures? Knowledge 3 UNIT V Express the different types of data used for cluster Understand 1. 3 analysis? 2. State K-Means method? Knowledge 1 3. Define Outlier Detection? Knowledge 3 4. Define Clustering? Knowledge 3 5. State hierarchical method? Knowledge 3

PART – B LONG ANSWER QUESTIONS

Blooms S. Course Questions Taxonomy No Outcome Level UNIT I Differentiate between descriptive and predictive data 1 Understand 3 mining? Explain data mining as a step in the process of 2 Understand 2 knowledge discovery? Describe briefly Discretization and concept hierarchy 3 Understand 2 generation for numerical data? List and describe the five primitives for specifying a 4 Knowledge 1 data mining task? Define data cleaning? Express the different techniques 5 Knowledge 1 for handling missing values? UNIT II Differentiate between descriptive and predictive data Understand 1. 1 2 mining? Explain data mining as a step in the process of Understand 2. 1 knowledge discovery? Describe briefly Discretization and concept hierarchy Knowledge 3. 2 generation for numerical data? List and describe the five primitives for specifying a Understand 4. 3 data mining task? 5. Define data cleaning? Express the different techniques Knowledge 3 MLR Institute of Technology, Dundigal, Hyd-500043 Page 82

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for handling missing values? UNIT III Discuss about mining multilevel association rules from Understand 1. 3 transaction databases in detail? Explain the Apriori algorithm with example? Understand 2. 2

Discuss the generating association rules from frequent Understand 3. 2 itemsets. Discuss the FP-growth algorithm? Explain with an Understand 4. 2 example? Apply the following rules on a database has five Apply transactions. Let min sup =60% and min con f = 80%

. 5. (a) Find all frequent itemsets using Apriori . 3 (b) List all of the strong association rules (with support s and confidence (c) matching the following metarule, where X is a variable representing customers, and itemi denotes variables representing items (e.g., “A”, “B”, etc.): ∀ x ∈ transaction, buys(X , item1) ∧ buys(X , item2) ⇒ buys(X , item3) [s, c] UNIT IV Describe the working procedures of simple Bayesian Knowledge 1. 2 classifier? 2. Discuss about basic decision tree induction algorithm? Understand 1 3. Explain Bayesian Belief Networks? Understand 2 Explain about the classification and prediction? Understand 4. 2 Example with an example? Explain briefly various measures associated with Understand 5. 2 attribute selection? UNIT V Explain about the agglomerative and divisive Understand 1. 2 hierarchical methods? 2. Discuss about the density-based outlier detection? Understand 3 Apply the given following measurements for the Apply variable age: 28, 32, 15, 42, 28, 43, 30, 32, 55, 26, 3. standardize the variable by the following: 3 (a) Compute the mean absolute deviation of age. (b) Compute the z-score for the first four measurements Define the distance-based outlier? Illustrate the Knowledge 4. efficient algorithms for mining distance-based 1 algorithm ? 5. Write algorithms for k-means and k-means? Explain? Understand 1

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PART – C (PROBLEM SOLVING AND CRITICAL THINKING QUESTIONS)

Blooms S. Course Questions Taxonomy No Outcome Level UNIT I Express the steps involved in data mining when 1. Creating 2 viewed as a process of knowledge discovery 2. Compare database and data warehouse. Analyze 1 Explain the difference and similarity between discrimination and classification, between 3. Apply 3 characterization and clustering, and between classification and regression. Examine three challenges to data mining regarding 4. Analyze 2 data mining methodology and user interaction issues. UNIT II Determine which of the association rule mining 1 Analyze 2 algorithms is efficient? Propose a technique that can improve the efficiency of 2 Evaluate 3 APRIORI algorithm? How effective is FP Growth algorithm in mining 3 Evaluate 2 association rules? Explain how the APRIORI and FP-Growth algorithm 4 Evaluate 2 are used to generate strong association rules? UNIT III Determine which of the association rule mining 1 Evaluate 2 algorithms is efficient? Propose a technique that can improve the efficiency 2 Creating 4 of APRIORI algorithm? How effective is FP Growth algorithm in mining 3 Evaluate 2 association rules? UNIT IV 1 Explain the Bayesian classification? Evaluate 2 2 Explain statistical perspective in data mining? Analyze 2 Choose the measures for selecting the best split 3 Evaluate 3 algorithm for decision tree induction? UNIT V How effective are Agglomerative methods and 1 Evaluate 3 divisive methods in hierarchical clustering? 2 Explain the portioning methods of clustering? Analyze 2 3 Determine the key issues in hierarchical clustering? Evaluate 3

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11.13 ASSIGNMENT QUESTIONS PART-A (SHORT ANSWER QUESTIONS)

Blooms S. Course Questions Taxonomy No Outcome Level UNIT-I 1. List out major issues in data mining. Knowledge 1 2. What is data mining task primitives Understand 1 3. Write about data reduction. Knowledge 2 UNIT II 1. Define OLAP,ROLAP,MOLAP Understand 2

2. Differentiate between ROLAP and MOLAP Knowledge 3 3. Explain Multidimensional OLAP (MOLAP) server? Understand 2 UNIT III 1. Define item set? Understand 1 2. Name the steps in association rule mining? Understand 1 3. Explain the join step? Knowledge 2 4. Describe the prune step? Knowledge 2 UNIT IV 6. Define the rule pruning? Understand 2 7. Explain the working of back propagation? Understand 1 8. Define the construction of Naïve Bayesian classification? Understand 3 9. Explain the If-Then rules for classification? Understand 2 UNIT V 6. Explain the types of data used for cluster analysis Understand 2 7. What do you mean by partitioning methods Understand 3 8. Define the clustering method? Knowledge 2 9. What do you mean by cluster analysis Understand 2

PART – B LONG ANSWER QUESTIONS

Blooms S. Course Questions Taxonomy No Outcome Level UNIT I 1 Discuss functionalities of data mining Apply 2 2 Diagram of KDD. Analyze 1 3 Differentiate between types of data sets. Evaluate 2 UNIT II 1. 1 Explain the characteristics of data warehouse? Evaluate 1 2. Explain the OLAP operations in multidimensional model Evaluate 4 Explain the various schematic representations in multidimensional 3. Evaluate 3 model? UNIT III Define the APRIORI principle. Explain how the algorithm is used 1. Knowledge 2 to generate strong association rules? Define the terms Frequent itemset, closed itemset and association 2. Knowledge 2 rules? Discuss which algorithm is influential for mining frequent item 3. Understand 2 set for Boolean association rules? Explain with an example

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Describe different techniques to improve the efficiency of 4. Knowledge 3 APRIORI algorithm. Explain? 5. Discuss the FP – Growth algorithm? Explain with an example Understand 3 UNIT IV 1 Explain the training of Bayesian belief networks? Knowledge 2 Explain how decision tree pruning work? What are the 2 Knowledge 2 enhancements to the basic decision tree induction? Explain about classification and prediction? Explain with an 3 Knowledge 3 example? 4 Discuss about decision tree induction algorithm Knowledge 3 UNIT V 1. Explain the basic agglomerative hierarchical algorithm? Knowledge 2 2. Explain the agglomerative method and divisive method? Knowledge 2 3. Describe the PAM algorithm in detail Knowledge 2 4. Explain the evaluation of clustering algorithm? Knowledge 3

PART – C (PROBLEM SOLVING AND CRITICAL THINKING QUESTIONS)

Blooms S. Course Questions Taxonomy No Outcome Level UNIT I Explain the two different types of OLAP server architectures 1. Analyzing 2 with diagram? Explain the role of OLAP server, meta data in 3- tier 2. Evaluate 1 architecture of a data warehouse system? Differentiate between fully addictive, semi addictive and non- 3. Analyzing 1 addictive measures? UNIT II 1 What are the motivating challenges in the area of data mining? Evaluate 3 Explain the concept of discretization and binaryzation with an 2 Analyzing 3 example? 3 Explain the concept of feature subset selection with an example? Analyzing 4 UNIT III How effective is FP Growth algorithm in mining association 1 Evaluate 3 rules? Explain how the APRIORI and FP-Growth algorithm are used to 2 Analysis 4 generate strong association rules? Determine which of the association rule mining algorithms is 3 Evaluate 3 efficient? UNIT IV 1 Explain K-nearest neighbor classification-algorithm? Analysis 2 2 Explain the Bayesian classification? Analysis 2 3 Explain statistical perspective in data mining? Analysis 2 UNIT V 1 Explain the PAM algorithm? Analyzing 3 How effective are Agglomerative methods and divisive methods 2 Evaluate 1 in hierarchical clustering? 3 Explain the key issues in hierarchical clustering? Analyzing 3

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12. BIG DATA ANALYTICS (A10547)

12.0COURSE DESCRIPTION

Course Title BIG DATA ANALYTICS Course Code A10547(Professional Elective – 2) Regulation R13 Lectures Tutorials Practical Credits Course Structure 3 1 - 3 Course Coordinator Mrs.N.Shirisha, Asst. Professor, CSE Mr. Sai Prasad, Asst. Professor, CSE Team of Instructors Mr.B.Anand Kumar, Asst. Professor, CSE Dr.B.Rama, Assoc. Professor, CSE

12.1 COURSE OVERVIEW:

Data analysis is the process of data analyzing and extracting useful information which can help in making useful business decisions. As part of this course Big Data tools and Data Visualization tools are introduced.

12.2 PREREQUISITES:

Level Credits Periods/Weeks Prerequisites UG 3 5 IA-1

12.3 MARKS DISTRIBUTION:

University End Total Session Marks (25M) Exam Marks Marks Mid Semester Test There shall be two midterm examinations. Each midterm examination consists of subjective type and objective type tests. The subjective test is for 10 marks of 60 minutes duration. Subjective test of shall contain 4 questions; the student has to answer 2 questions, each carrying 5 marks. The objective type test is for 10 marks of 20 minutes duration. It consists of 10 Multiple choice and 10 objective type questions, the 75 100 student has to answer all the questions and each carries half mark. First midterm examination shall be conducted for the first two and half units of syllabus and second midterm examination shall be conducted for the remaining portion. Assignment Five marks are earmarked for assignments. There shall be two assignments in every theory course. Marks shall be awarded considering the average of two assignments in each course.

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12.4 EVALUATION SCHEME:

S. No Component Duration Marks 6. I Mid Examination 80 minutes 20

7. I Assignment --- 5

8. II Mid Examination 80 minutes 20

9. II Assignment ---- 5

10. External Examination 3 hours 75

12.5 COURSE OBJECTIVES: I. To introduce the terminology, technology and its applications II. To introduce the concept of Analytics and Visualization III. To demonstrate the usage of various Big Data tools and Data Visualization tools

COURSE OUTCOMES:

At the end of the course students will able to: 1. Identify basic terminology of HADOOP, SPARK, IMPALA etc 2. Analyze the importance of Analytics in business perspective 3. Apply Big Data tools and Visualization tools

12.6 HOW PROGRAM OUTCOMES ARE ASSESSED:

Proficiency Program Outcomes Level assessed by

An ability to apply the knowledge of mathematics, Computing, Science Assignments, A H and engineering to solve Computer Science and Engineering problems Tutorials, Exams

An ability to design and conduct engineering experiments, as well as to B S Assignment s, tutorials analyze and interpret data.

An ability to design and construct a hardware and software system, C H Assignment s, Tests component, or process to meet desired needs, within realistic constraints

Graduates will demonstrate an ability to visualize and work on laboratory D N ------and Multi-disciplinary tasks individually or as a member within the teams An ability to demonstrate skills to use the techniques, modern E engineering Tools, Software and equipment necessary to analyze H Assignment s, Tests computer engineering Problems

F An understanding of professional, social and ethical responsibility S Lectures

An ability to recognize the global issues like green initiatives and G alternate energy sources and to take technology to villages and to S ------recognize the rural requirements

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The broad education necessary to understand the impact of engineering H N Lectures solutions in a global, economic, environmental, and societal context Graduate will develop confidence for self-education and acquire new Assignment s, Tutorials, I knowledge in the computing discipline and ability and practice for Multi- H Exams disciplinary tasks as a member within the teams Assignment s, Tutorials, J To communicate effectively N Exams

An ability to use the techniques, skills and modern engineering tools Assignment s, Tutorials, K H necessary for Engineering practice Exams

Graduates are able to participate and succeed in competitive examination Assignment s, Tutorials, L N like GRE, GATE, TOEFL, GMAT etc. Exams The use of current application software and the design and use of operating systems and the analysis, design, testing and documentation of Assignment s, Tutorials, M H computer programs for the use in Computer Science and engineering Exams technologies. N=None S=Supportive H=Highly Related

12.7 SYLLABUS:

UNIT I Data Management (NOS 2101) Design Data Architecture and manage the data for analysis, understand various sources of Data like Sensors/signal/GPS etc. Data Management, Data Quality (noise, outliers, missing values, duplicate data) and Data Preprocessing. Export all the data onto Cloud ex. AWS/Rackspace etc. Maintain Healthy, Safe & Secure Working Environment (NOS 9003) Introduction, workplace safety, Report Accidents & Emergencies, Protect health & safety as your work, course conclusion, and assessment UNIT II Big Data Tools (NOS 2101) Introduction to Big Data tools like Hadoop, Spark, Impala etc., Data ETL process, Identify gaps in the data and follow-up for decision making. Provide Data/Information in Standard Formats (NOS 9004) Introduction, Knowledge Management, Standardized reporting & compliances, Decision Models, course conclusion. Assessment UNIT III Big Data Analytics: Run descriptive to understand the nature of the available data, collate all the data sources to suffice business requirement, Run descriptive statistics for all the variables and observer the data ranges, Outlier detection and elimination. UNIT IV Machine Learning Algorithms (NOS 9003) Hypothesis testing and determining the multiple analytical methodologies, Train Model on 2/3 sample data using various Statistical/Machine learning algorithms, Test model on 1/3 sample for prediction etc. UNIT V (NOS 9004) Data Visualization (NOS 2101) Prepare the data for Visualization, Use tools like Tableau, QlickView and D3, Draw insights out of Visualization tool.

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Product Implementation TEXT BOOKS: 1. Student’s Handbook for Associate Analytics.

REFERENCE BOOKS: 1. Introduction to Data Mining, Tan, Steinbach and Kumar, Addison Wesley, 2006 2. Data Mining Analysis and Concepts, M. Zaki and W. Meira (the authors have kindly made an online version available): http://www.dataminingbook.info/uploads/book.pdf 3. Mining of Massive Datasets Jure Leskovec Stanford Univ. AnandRajaramanMilliway Labs Jeffrey D. Ullman Stanford Univ. (http://www.vistrails.org/index.php/Course:_Big_Data_Analysis)

12.8 COURSE PLAN:

Lecture Blooms Course Learning Outcomes Topics to be covered Reference No. Level 1. By the end of the session the Data Management :Design Data student can Build Architecture and manage the data Level 3 & the Design Data Architecture for analysis 1 2. By the end of the session the student will demonstrate the Level 2 Design Data Architecture 1. By the end of the session the Design Data Architecture student can Build Level 3 & the Design Data Architecture 2 2. By the end of the session the student will demonstrate the N Level 2 Design Data Architecture A 1.By the end of the session the understand various sources of Data S student can make use of various like Sensors/signal/GPS etc. S sources of Data like Sensors C O 3 /signal/GPS etc. Level 3 2. By the end of the session the M student can explain the various M sources of Data like Sensors A /signal/GPS etc. T By the end of the session the Data Management E 4 student can discuss Data R Level 6 Management I By the end of the session the Data Quality (noise, outliers, A 5 student can explain the Data missing values, duplicate data) L Level 2 Quality 1. By the end of the session the Data Preprocessing. 6 student can Illustrate the Data Level 2 Preprocessing 1. By the end of the session the Export all the data onto Cloud ex. 7 student can Utilize Exporting all AWS/Rackspace etc. Level 3 the data onto Cloud ex. 1.By the end of the session the Maintain Healthy, Safe & Secure student can Understand to Working Environment 8 Maintain Healthy, Safe & Level 3 Secure Working Environment

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2. By the end of the session the student can measure the Secure Level 5 Working Environment 1.By the end of the session the workplace safety student can contrast the 9 workplace safety Level 4

1.By the end of the session the Report Accidents & Emergencies Level 6 student can dsicuss on the

10 importance Report Accidents 2.By the end of the session the student can analyse Emergencies Level 4 1.By the end of the session the Protect health & safety as your student can relate the importance work Level 2 of Protect health &

safety as your work 11 2. By the end of the session the student can simplify the safety of your work. Level 4

1.By the end of the session the course conclusion, and assessment Level 6 12 student can plan to perform class

activity. By the end of the session the Introduction to Big Data tools like 13 student Understand the basic Hadoop Level 3 N functioning of hadoop tool A By the end of the session the Introduction to Big Data tools like S 14 student Understand the basic Spark, Level 3 S functioning of Spark tool C By the end of the session the Introduction to Big Data tools like O 15 student Understand the basic Impala etc M Level 3 functioning of Impala tool M By the end of the session the Data ETL process A 16 student can Understand the T Level 3 process of Data ETL E By the end of the session the Identify gaps in the R 17 student can Understand how to I Level 3 identify gaps in the data data A By the end of the session the follow-up for decision making. L student can classify how to 18 identify gaps in the data and Level 4 what are the follow-ups for filling the gaps 1. By the end of the session the Provide Data/Information in 19 student can assume the Standard Formats Level 4 data standard formats 1.By the end of the session the Introduction to 20 student can illustrate the concept Knowledge Management Level 2 of Knowledge Management By the end of the session the Standardized reporting & student can outline the compliances 21 Level 2 Standardized process for reporting & compliances

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By the end of the session the 22 student can Understand some of Decision Models,. Level 2 the decision models 1.By the end of the session the course conclusion 23 student can Understand the Level 2 importance of the course 1.By the end of the session the 24 student can plan to perform class Assessment Level 6s activity By the end of the session the Introduction to Big Data Analytics 25 student Understand the Level 3 introduction about BDA By the end of the session the Run descriptive to understand the student Understand the nature of nature of the available data 26 the available data Level 2

By the end of the session the collate all the data sources to 27 student Understand how to suffice business requirement Level 3 collate all the data sources By the end of the session the Run descriptive statistics for all the N student can Understand how to variables 28 A Level 4 run descriptive statistics S By the end of the session the observer the data ranges S C 29 student can Understand the data Level 6 ranges O M By the end of the session the Outlier detection M 30 student can Understand the A Level 6 concept of outlier detection T By the end of the session the Outlier elimination. E 31 student can Understand the R Level 2 concept of outlier elimination I 1.By the end of the session the course conclusion A 32 student can Understand the L Level 3 importance of the course 1.By the end of the session the Assessment 33 student can plan to perform class Level 6 activity 1.By the end of the session the Introduction to Machine Learning 34 student can Explain the concepts Algorithms Level 2 of ML algorithms By the end of the session the Hypothesis testing 35 student can experiment with the Level 3 Hypothesis testing By the end of the session the determining the multiple analytical student can determine the methodologies 36 Level 5 Multiple analytical methodologies By the end of the session the Train Model on 2/3 sample data 37 student can Understand Train using various Statistical/Machine Level 3 Model on 2/3 sample data learning algorithms By the end of the session the Test model on 1/3 sample for N 38 student can Understand Train prediction etc A Level 3 Model on 1/3 sample data S 1.By the end of the session the course conclusion S 39 student can Understand the C Level 3 importance of the course O

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1.By the end of the session the Assessment M 40 student can plan to perform class M Level 6 activity A By the end of the session the Introduction to Data Visualization T 41 student elaborate the introduction E Level 6 about data visualization R By the end of the session the Prepare the data for Visualization I 42 student conclude how to prepare A Level 5 data for visualization. L By the end of the session the Use tools like Tableau 43 student can test the basic Level 6 functions of Tableau tool. By the end of the session the Use tools like QlickView 44 student can explain the basic Level 2 functions of QlickView tool. By the end of the session the Use tools like D3 45 student can determine the basic Level 5 functions of D3 tool By the end of the session the Draw insights out of Visualization student can Understand the tool. 46 Level 3 concept of draw insights out of Visualization tool. By the end of the session the Product Implementation 47 student can Understand the Level 3 product implementation 1.By the end of the session the course conclusion 48 student can Understand the Level 3 importance of the course 1.By the end of the session the Assessment 49 student can plan to perform class Level 6 activity

12.9 MAPPING COURSE OBJECTIVE LEADING TO THE ACHIEVEMENT OF COURSE OUTCOMES:

Course Outcomes Course Objective 1 2 3 I H H II S H S III H H S=Supportive H=Highly Related 12.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF P ROGRAM OUTCOMES: Program Outcomes Course Outcomes A B C D E F G H I J k L M

1 H H H S H H H S H H

2 S H S S H S S H S

3 H H H H H H H H S=Supportive H=Highly Related

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12.11 OBJECTIVE BITS: UNIT-I 1. Amazon S3 is which type of storage service? A. Object B. Block C. Simple D. secure 2. Amazon ______cloud-based storage system allows you to store data objects ranging in size from 1 byte up to 5GB. A. S1 B. S2 C. S3 D. S4 2. Which of the following can be done with S3 buckets through the SOAP and REST APIs? A. Upload new objects to a bucket and download them B. Create, edit, or delete existing buckets C. Specify where a bucket should be stored D. All of the mentioned 3. Why is a bucket policy necessary? A. To allow bucket access to multiple users. B. To grant or deny accounts to read and upload files in your bucket C. To approve or deny users the option to add or remove buckets D. All of the above 4. Which of the following statement is wrong about Amazon S3? A. Amazon S3 is highly reliable B. Amazon S3 provides large quantities of reliable storage that is highly protected C. Amazon S3 is highly available D. None of the mentioned 5. Process of arranging data into a new order is called A. manipulation of data B. standardized information C. standardized input D. standardized documents 6. Various operations that are carried on data while processing it includes A. calculation B. analysis C. manipulation D. all of above 7. Information is A. Data B. Processed Data C. Manipulated input D. Computer output 9. Data by itself is not useful unless A. It is massive B. It is processed to obtain information C. It is collected from diverse sources D. It is properly stated 10. For taking decisions data must be

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A. Very accurate B. Massive C. Processed correctly D. Collected from diverse sources 11. Decision support systems are used for A. Management decision making B. Providing tactical information to management C. Providing strategic information to management D. Better operation of an organization 12. Decision support systems are used by A. Line managers. B. Top-level managers. C. Middle level managers. D. System users 13. Decision support systems are essential for A. Day–to-day operation of an organization. B. Providing statutory information. C. Top level strategic decision making. D. Ensuring that organizations are profitable. 14. The quality of information which does not hide any unpleasant information is known as A. Complete B. Trustworthy C. Relevant D. None of the above 15. The quality of information which is based on understanding user needs A. Complete B. Trustworthy C. Relevant D. None of the above 16. Online transaction processing is used because A. it is efficient B. disk is used for storing files C. it can handle random queries. D. Transactions occur in batches 17. On-line transaction processing is used when i) it is required to answer random queries ii) it is required to ensure correct processing iii) all files are available on-line iv) all files are stored using hard disk A. i ,ii B. b i, iii C. c ii ,iii, iv D. d i , ii ,iii 18. Off-line data entry is preferable when i) data should be entered without error ii) the volume of data to be entered is large iii) the volume of data to be entered is small iv) data is to be processed periodically A. i, ii

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B. ii, iii C. ii, iv D. iii, iv 19. Batch processing is used when i) response time should be short ii) data processing is to be carried out at periodic intervals iii) transactions are in batches iv) Transactions do not occur periodically A. i ,ii B. b. i ,iii,iv C. c. ii ,iii D. d. i , ii ,iii 20. Data mining is used to aid in A. operational management B. analyzing past decision made by managers C. detecting patterns in operational data D. retrieving archival data

UNIT-II 1. Hdfs files are designed for: A - Multiple writers and modifications at arbitrary offsets. B - Only append at the end of file C - Writing into a file only once. D - Low latency data access. 2. When a file in HDFS is deleted by a user A - it is lost forever B - It goes to trash if configured. C - It becomes hidden from the user but stays in the file system D - File sin HDFS cannot be deleted 3. Which one is not one of the big data feature? A - Velocity B - Veracity C - volume D - variety 4. The hdfs command put is used to A - Copy files from local file system to HDFS. B - Copy files or directories from local file system to HDFS. C - Copy files from from HDFS to local filesystem. D - Copy files or directories from HDFS to local filesystem 5. The command to check if Hadoop is up and running is − A. A - Jsp B. B - Jps C. C - Hadoop fs –test D. D - None 6. Which of the following are among the duties of the Data Nodes in HDFS? A - Maintain the file system tree and metadata for all files and directories. B - None of the options is correct. C - Control the execution of an individual map task or a reduce task. D - Store and retrieve blocks when told to by clients or the NameNode. E - Manage the file system namespace.

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7. The hadoop frame work is written in A - C++ B - Python C - Java D - GO 8. Which one of the following stores data? A - Name node B - Data node C - Master node D - None of these 9. Which demon is responsible for replication of data in Hadoop? A - HDFS. B - Task Tracker. C - Job Tracker. D - Name Node. E - Data Node. 10. The inter process communication between different nodes in Hadoop uses A - REST API B - RPC C - RMI D - IP Exchange 11. A ______node acts as the Slave and is responsible for executing a Task assigned to it by the JobTracker. A. MapReduce B. Mapper C. TaskTracker D. JobTracker 12. Point out the correct statement : A. MapReduce tries to place the data and the compute as close as possible B. Map Task in MapReduce is performed using the Mapper() function C. Reduce Task in MapReduce is performed using the Map() function D. All of the mentioned 13. ______part of the MapReduce is responsible for processing one or more chunks of data and producing the output results. A. Maptask B. Mapper C. Task execution D. All of the mentioned 14. ______function is responsible for consolidating the results produced by each of the Map() functions/tasks. A. Reduce B. Map C. Reducer D. All of the mentioned 15. ______is a utility which allows users to create and run jobs with any executables as the mapper and/or the reducer. A. Hadoop Strdata B. Hadoop Streaming C. Hadoop Stream D. None of the mentioned

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16. ______maps input key/value pairs to a set of intermediate key/value pairs. A. Mapper B. Reducer C. Both Mapper and Reducer D. None of the mentioned 17. The number of maps is usually driven by the total size of : A. Inputs B. outputs C. tasks D. None of the mentioned 18. Which of the following command is used to show values to keys used in Pig ? A. set B. declare C. display D. All of the mentioned 19. Use the ______command to run a Pig script that can interact with the Grunt shell (interactive mode). A. Fetch B. declare C. run D. All of the mentioned 20. Spark was initially started by ______at UC Berkeley AMPLab in 2009. A. Mahek Zaharia B. Matei Zaharia C. Doug Cutting D. Stonebraker 21. Point out the correct statement : A. RSS abstraction provides distributed task dispatching, scheduling, and basic I/O functionalities B. For cluster manager, Spark supports standalone Hadoop YARN C. Hive SQL is a component on top of Spark Core D. None of the mentioned 22. ______is a component on top of Spark Core. A. Spark Streaming B. Spark SQL C. RDDs D. All of the mentioned 23. 4. Spark SQL provides a domain-specific language to manipulate ______in Scala, Java, or Python. A. Spark Streaming B. Spark SQL C. RDDs D. All of the mentioned 24. ______is a fully integrated, state-of-the-art analytic database architected specifically to leverage strengths of Hadoop. A. Oozie B. Impala C. Lucene D. BigTop 25. 2. Point out the correct statement :

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A. With Impala, more users, whether using SQL queries or BI applications, can interact with more data B. Technical support for Impala is not available via a Cloudera Enterprise subscription C. Impala is proprietary tool for Hadoop D. None of the mentioned 26. Impala is an integrated part of a ______enterprise data hub. A. Micro Soft B. IBM C. Cloudera D. All of the mentioned View Answer 27. For Apache ______users, Impala utilizes the same metadata. A. Takes B. Hive C. Pig D. Oozie 28. Which file contains information about configuration of dataset in ETL system? A. Data File B. Configuration File C. Descriptor File D. Control File 29. Which testing type is used to check the data type and length of attributes in ETL transformation? A. Production Validation Testing B. Data Accuracy Testing C. Metadata Testing D. Data Transformation testing 30. Which type of system captures, organizes, and disseminates knowledge? A. Tactical information systems B. Artificial intelligence systems C. Decision support systems D. Knowledge management systems

UNIT-III 1. Which of the following provides a measure of central location for the data? A. standard deviation B. mean C. variance D. range 2. A numerical value used as a summary measure for a sample, such as sample mean, is known as a: A. population parameter B. sample parameter C. sample statistic D. population mean 3. Given the formula for the Coefficient of Variation = ×100

The hourly wages of a sample of 130 system analysts are given: What does the coefficient of variation equal?

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mean = 60 mode = 73 median = 74 range = 20 variance = 324 A. 0.30% B. 30% C. 5.4% D. 54% 4. The variance of a sample of 169 observations equals 576. The standard deviation of the sample equals: A. 13 B. 24 C. 576 D. 28,461 5. The median of a sample will always equal the: A. mode B. mean C. 50th percentile D. all of the above answers are correct 6. The median is a measure of: A. relative dispersion B. absolute dispersion C. central location D. relative location 7. The 75th percentile is referred to as the: A. first quartile B. second quartile C. third quartile D. fourth quartile 8. The difference between the largest and the smallest data values is called the: A. variance B. interquartile range C. range D. coefficient of variation 9. The first quartile: A. contains at least one third of the data elements. B. is the same as the 25th percentile. C. is the same as the 50th percentile. D. is the same as the 75th percentile. 10. Which of the following is not a measure of central tendency? A. mean B. median C. variance D. mode 11. Which of the following is a measure of dispersion? A. percentiles B. quartiles C. interquartile range D. all of the above are measures of dispersion

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12. The most frequently occurring value of a data set is called the: A. range B. mode C. mean D. median 13. The interquartile range is: A. the 50th percentile. B. another name for the variance. C. the difference between the largest and smallest values. D. the difference between the third quartile and the first quartile. 14. When the data are skewed to the right, the measure of Skewness will be: A. negative B. zero C. positive D. one

UNIT-IV 1. The most popular test conducted for examining hypotheses about variances is the ____. A. F-test B. p-test C. t-test D. z-test E. chi-square 2. The ____ is a statistic that assumes that the variable has a symmetric bell-shaped distribution and the mean is known, and the population variance is known. A. a statistic B. p statistic C. F statistic D. z statistic E. bell statistic 3. The ____ is a symmetric bell-shaped distribution that is useful for small samples or when variance is unknown. A. F distribution B. p distribution C. t distribution D. z distribution E. chi-square distribution 4. Two samples that are related are best referred to as ____. A. paired samples B. dependent samples C. parallel samples D. exclusive samples E. non-experimental samples 5. A(n) ____ of sample variance may be performed if it is not known whether the two populations have equal variance. A. p-test B. t-test C. z-test D. chi-square test

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E. none of the above is correct 6. Examples of hypotheses related to paired samples include all of the following EXCEPT: A. Shoppers consider brand name to be more important than price while purchasing fashion clothing. Households spend more money on pizza than they do on hamburgers. B. The proportion of households who subscribe to a daily newspaper exceeds the proportion subscribing to magazines. C. Male consumers spend more on a product than do female consumers. D. The proportion of a bank's customers who have a checking account exceeds the proportion who has a savings account. 7. The ____ is a statistic that assumes that the variable has a symmetric bell-shaped distribution and the mean is known, and the population variance is unknown. A. t statistic B. p statistic C. F statistic D. z statistic E. bell statistic 8. ______is a statistical procedure for analyzing associative relationships between two metric variables. A. Analysis of variance B. Covariance analysis C. Deviation analysis D. Correlation analysis E. Functional linear analysis 9. The term used to denote the standardized regression coefficient in multiple regression is called the ______coefficient. A. alpha B. beta C. gamma D. theta E. partial regression 10. According to the text, hypotheses related to differences in population means if the population variance is known can be tested using the ____. A. F distribution B. p distribution C. t distribution D. z distribution E. chi-square distribution 11. The 50th percentile is: A. The third quartile B. The lower quartile C. The value half way along the entire range of the scale D. The median 12. The standard deviation is the: A. Square of the variance B. Square root of the variance C. Average of all the deviations of scores from the mean D. Average of the square roots of the deviations of scores from the mean 13. The analysis of data on multiple responses:

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A. Can be handled like any other set of multivariate data B. Is necessitated when the respondent to a questionnaire may check two or more items in a list of responses C. Presents no special problems for statistical analysis D. Can present special problems with interpretation and statistical testing 14. Percentiles are most conveniently computed using: A. Analyze>Nonparametric Tests>One-Sample Nonparametric Tests B. Analyze>Compare Means>Means C. Analyze>Descriptive Statistics>Crosstabs D. Analyze>Descriptive Statistics>Frequencies 15. A histogram: A. Is a graphic representation of the frequency distribution of a continuous variable B. Is a graphic representation of the frequency distribution of a qualitative or categorical variable C. Is an alternative to a pie chart D. Is a bar chart 16. Which of the following statements is true? A. The standard deviation can take a negative value B. The variance and standard deviation are always appropriate descriptive measures for any set of continuous or scale data C. The variance and standard deviation are measures of spread or dispersion D. If each of a set of scores is multiplied by a constant (say 2), the value of the standard deviation increases fourfold 17. The mean, the median and the mode: A. Are all measures of central tendency B. Are all applicable to continuous or scale data only C. Are all suitable equivalent measures of the average, irrespective of the distribution D. Always have values that are very similar when calculated from the same data set

UNIT-V 1) When you design a sheet, which option can reduce the amount of space needed by allowing the same chart to be displayed by different dimensions? A. Cyclic group B. Lookup Dimension C. Layer Expression D. Multi Box 2) Which type of Qlikview object cannot be configured with any trigger actions? A. Gauge B. Text Object C. Sheet D. List Box 3) Which visualization method is being used in this series of numbers to highlight those of interest? (Refer image 1) A. Cherry Picking B. Exaggeration C. Preattentive Perception D. Visual Grouping 4) Which is the correct order of the visualization design process? A. Platforms, Information Design, Visual Design, Testing, Users & Context B. Platforms, Visual Design, Information Design, User & Context, Testing

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C. User & Context, Information Design, Platforms, Visual Design, Testing D. User & Context, Platforms, Information Design, Visual Design, Testing 5) Which is NOT a good method for gathering user information? A. Questionnaires B. Interviews C. Field Studies D. Preconceptions 6) Compare the two charts shown. What is the main visualization advantage of displaying the line to join the data points? A. None, they both show same information B. the line stop human enclosure hiding the outlier C. The line display the correct sequence of the data point D. the line exaggerates the chart trend 7) Which data category is not represented by the attributes in this example? A. Nominal Data B. Ordinal Data C. Interval Data D. Ratio Data 8) Why would you be careful when encoding nominal data using red and green? A. They should only be used with traffic light chart types B. They make a charts look ugly due to the contrast in color C. Because approximately 10% of the male population are red-green colorblind D. Color choice makes no difference so long as the representation looks good 9) DAR is a Qlikview design concept. Which is the correct list of words which make up this acronym? A. Dash boards, Analysis, Reports B. Data, Accumulation, Results C. Design, Architecture, Reports D. Direct Access Reporting E. Don't know 10) Which is the best chart type to represent ranked data, such as Sales by Region? A. Horizontal Bar Chart B. Pie chart C. Combo chart D. Pivot table E. Don't know 11) Which display method is being used by this report? A. Color mix B. Dynamic Colors C. Silent Legend D. Color emphasis E. Don't know 12) In your Qlik View application, How would you create a button that toggles a help layer on or off? A. Use a chart Extension Object B. Set a variable with the button and use conditional show on the help objects C. Use the Button to control the layer properties of the help objects D. Link the button to the pop up property of the help objects E. Don't know

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12.12 ASSIGNMENT QUESTION BANK PART A (SHORT ANSWER QUESTIONS)

Blooms Course S. No Questions Taxonomy Outcome Level UNIT –I 16. Define Data management Knowledge A

17. Difference between data preprocessing and data cleaning Analysis B

18. Define Data de-duplication and data validation Knowledge A

19. Differentiate between Big data and data mining Analysis B

20. What would happen if data is so big to preprocess with existing tools? Synthesis C

21. Explain data architecture. Comprehension D

22. Explain the various data sources. Comprehension A

23. Define cloud Knowledge E

24. Define Hazards. Knowledge A

25. Define Accidents. Knowledge E

26. Define Emergencies. Knowledge B

27. Differentiate accident and emergency. Analysis C

28. Describe survey method. Knowledge A

29. Describe Latin square design. Knowledge B

30. Distinguish structured and unstructured observation Comprehension C

UNIT –II 11. Distinguish Big data and hadoop Comprehension E

12. Define Hadoop. Knowledge E

13. Define HDFS? Knowledge A

14. Distinguish HDFS and Map reduce. Comprehension B

15. List the various bigdata tools. Knowledge C

16. Differentiate Distributed and parallel computing. Analysis A

17. Define MapReduce. Knowledge B

18. List deamons of hadoop. Knowledge A

19. Define Jobtracker and task tracker. Knowledge C

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20. Define Spark and scala? Knowledge e

UNIT -III

7. Define bigdata analytics Knowledge A

8. Differentiate RDBMS and Column based data bases. Analysis B

9. Define key value store Knowledge B

10. Define descriptive statistics. Knowledge A

11. Define document based data bases Knowledge C

12. Differentiate graph data bases vs Document based databases. Analysis D

UNIT –IV

1 Define supervised learning. Knowledge A

2 Define un supervised learning. Knowledge A

3 Define machine learning. Knowledge B

4 Differentiate supervised and un supervised learning Analysis C

5 Differentiate train set and test set. Knowledge B

Compare the various machine learning algorithms and investigate which 6 Analysis D can be best used for prediction 7 How can we predict the Analysis report using R tools Create E

8 Define K means algorithm Knowledge A

9 Define Naïve bayes algorithm. Knowledge B

10 Predict an analysis for 2/3 train set and 1/3 test set Knowledge C

UNIT –V

1 Give the meaning visualization Comprehension A

2 Define Tableau. Knowledge A

3 List various visualization tools. Knowledge A

4 Define Qlickview. Knowledge B

5 Define planning. Knowledge A

6 Explain how to enhance your data using Tableau tool Comprehension C

7 List things to prepare a data for visualization. Knowledge D

8 Define D3 tool? Knowledge E

9 Take a sample set and show the process of data visualization Application E

PART B (LONG ANSWER QUESTIONS)

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Blooms S. Course Question Taxonomy No Outcome Level

UNIT –I

1. Discuss various data management processes Comprehension A

2. List the various sources of data and explain them Knowledge B

3. Explain the data design architecture and its components Comprehension, A Synthesis, 4. Explain the various tools of cloud to import and export data into cloud Comprehension,Evaluation B Synthesis, 5. Show the process of importing a file into Amazon S3 cloud ApplicationEvaluation C

6. Show the process of creating buckets in Amazon S3 Application, D Synthesis 7 List the various work place safety guidelines Knowledge E

8 Explain the procedure to handle accidents and emergencies? Knowledge A

9 What are the potential sources of hazards in an organization Knowledge C Comprehension, 10 Explain the factors constituting healthy living Synthesis, e Evaluation UNIT –II

1. Define Big data and address the challenges of Big Data Knowledge A

2. Explain in detail the architecture of Hadoop Comprehension, B Synthesis, 3. Explain the steps to read a file in HDFS ComprehensionEvaluation B

4. Explain the steps to Write a file in HDFS Comprehension C

5. Write a note on Various big data tools. Application, D Synthesis 6. Explain the data flow process of Mapreduce Comprehension, D Synthesis, 7 Explain the role of Spark in making an Hadoop a solution for big data ComprehensionEvaluation D

8 What are the various competitors in market to find a solution for Knowledge E bigdata 9 Explain the Massive Parallel processing using Cloud era Impala Comprehension A

10 What is the importance of Knowledge management Knowledge B

11 Explain the architecture of OODA loop sequence Comprehension E

UNIT –III

1. Explain the transformation of relational databases to big data Comprehensi A on 2. Explain the design issues of Column based data basses. Comprehensi B on, 3 Discuss about Data pre processing for analysis. Synthesis,Comprehensi C Evaluationon 4 Explain the data division process in Map Reduce. Comprehensi D on 5 Discuss with suitable examples Graph based data bases Knowledge E

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6 What are outliers and how do we detect them Comprehensi A on 7 Explain Descriptive analytics in Big Data analytics Comprehensi B on, UNIT –IV Synthesis, Evaluation 1. Describe the various machine learning algorithms Knowledge, A Comprehensi 2. Describe Hypothesis testing. on,Knowledge, B EvaluationComprehensi 3. Describe the multiple analytical methodologies on,Knowledge, C EvaluationComprehensi 4. Explain support vector machines on,Comprehensi D Evaluationon 5. Explain the procedure to explore chosen algorithms for accuracy Application, E Synthesis 6. What are steps followed in Machine Learning Algorithm? Knowledge E

UNIT – V

1 Write down steps involved in Data Visualization In Tableu. Application, A Synthesis 2 What is the role of Tableu in Data Visualization? Application, B Synthesis 3 Why do we use Data Visualization? Application, B Synthesis 4 Understanding data and creation of dictionary Knowledge C

5 Explain Analysis and modeling Comprehensi D on

PART C (CRITICAL THINKING QUESTIONS)

Blooms Course S. No Question Taxonomy Outcome Level UNIT –I

1 Take a sample data and design a data flow process for that data Comprehension D Application, 2 Take a sample data and upload it into cloud Amazon S3 B Synthesis Take a sample data and upload it into cloud and provide permissions Application, 3 D in Amazon S3 Synthesis UNIT -II List the advantages Hadoop can provide for big data over traditional 1 Knowledge D sytems 2 What are the core components in Hadoop explain their work flow Knowledge E

3 List the ecosystem of spark and explain them Knowledge B

UNIT –III Compare the various strategies which organizations consider for Analysis , 1 A effective knowledge management Evaluation Analysis , 2 Compare the various databases for analytics B Evaluation 3 Discuss descriptive analytics in Big data analytics Comprehension D

UNIT –IV

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1 Discuss the use of hypothesis testing in machine learning Comprehension D

2 Give an example algorithm for k means in machine learning Comprehension B

3 Sketch the importance of machine learning in analytics Understand E

UNIT -V Application, 1 Write advantages of qlik view A Synthesis List the various data visualization tools and their importance in big 2 Knowledge B data 3 Prove the advantages of Tableau over other visualization tools Understand D

4 Give example implementation and usage of Dash board in tableau Comprehension A

12.13 TUTORIALS QUESTION BANK GROUP - A (SHORT ANSWER QUESTIONS)

Blooms Course Taxonomy S. No Questions Outcome Level

UNIT –I 2. Define Data management Knowledge A

14. Difference between data preprocessing and data cleaning Analysis B 15. Define Data de-duplication and data validation Knowledge D 16. Differentiate between Big data and data mining Analysis A 17. What would happen if data is so big to preprocess with existing tools? Synthesis B 18. Explain data architecture. Comprehension D 19. Explain the various data sources. Comprehension A 20. Define cloud Knowledge B 21. Define Hazards. Knowledge D 22. Define Accidents, And write the types of accidents Knowledge A 23. Define Emergencies. Explain the various types of emergencies Knowledge A 24. Differentiate accident and emergency. Analysis B 25. Describe survey method. Knowledge C 26. Describe Factorial design Knowledge D 27. Distinguish structured and unstructured observation Comprehension E UNIT –II 21. Distinguish Big data and hadoop Comprehension A 22. Define Hadoop. Knowledge B 23. Define HDFS? Knowledge C 24. Distinguish HDFS and Map reduce. Comprehension D 25. List the various bigdata tools. Knowledge E 26. Differentiate Distributed and parallel computing. Analysis E

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27. Define Map Reduce. Knowledge A 28. List deamons of hadoop. Knowledge B 29. Define Job tracker and task tracker. Knowledge C 30. Define Spark and scala? Knowledge D UNIT -III 6. Define bigdata analytics Knowledge A 7. Differentiate RDBMS and Column based data bases. Analysis B 8. Define key value store Knowledge C 9. Define descriptive statistics. Knowledge D 10. Define document based data bases Knowledge E 6. Differentiate graph data bases vs Document based databases. Analysis E UNIT –IV 1 Define supervised learning. Knowledge A 2 Define un supervised learning. Knowledge B 3 Define machine learning. Knowledge C 4 Differentiate supervised and un supervised learning Analysis D 5 Differentiate train set and test set. Knowledge E 6 Compare the various machine learning algorithms and investigate which can be Analysis E best used for prediction 7 How can we predict the Analysis report using R tools Create A 8 Define K means algorithm Knowledge B 9 Define Naïve bayes algorithm. Knowledge C 10 Predict an analysis for 2/3 train set and 1/3 test set Knowledge D UNIT –V 1 Give the meaning visualization Comprehension A 2 Define Tableau. Knowledge B 3 List various visualization tools. Knowledge C 4 Define Qlickview. Knowledge D 5 Define planning. Knowledge E 6 Explain how to enhance your data using Tableau tool Comprehension A 7 List things to prepare a data for visualization. Knowledge B 8 Define D3 tool? Knowledge C 9 Take a sample set and show the process of data visualization Application D

GROUP - II (LONG ANSWER QUESTIONS

Blooms Course S. No Questions Taxonomy Outcome Level UNIT –I

1 Discuss about primary sources of data Comprehension A

2 List the various secondary sources of data Knowledge B

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Comprehension, 3 Explain data design architecture and its components Synthesis, C Evaluation Comprehension, 4 Explain in detail about various stages in data collection and management. Synthesis, D Evaluation 5 Import various types of data into Cloud using amazon S3 Application E

6 Export data from cloud using amzon s3 Application, E Define various types of accidents and emergencies and guidelines 7 Knowledge A to identify and report them. 8 Define hazard, Explain potential sources of hazards in an organization Knowledge B Discuss the significance of work place safety and create awareness on 9 Knowledge C basic safety guidelines Comprehension, 10 Explain the role of analytics for effective data management Synthesis, D Evaluation UNIT -II Define big data and explain various challenges about traditional systems 1 Knowledge A and give a solution to overcome them. Comprehension, 2 Explain in detail Daemons of Hadoop Synthesis, B Evaluation 3 Discuss the processing mechanism in Hadoop Comprehension C

4 Define HDFS and explain its block size and replication factor Knowledge D Application, 5 Write a note on phases of mapreduce E Synthesis Comprehension, 6 Explain the role of spark in Managing bigdata Synthesis, E Evaluation 7 What are the advantages of spark and explain its eco system Knowledge A

8 Define Scala and explain its role in Big data Knowledge B

9 Explain the concept of Cloudera impala along with its features Knowledge A

10 List the various decision models and explain them briefly. Knowledge B

UNIT -III

1 Define analytics and Explain the role of analytics for big data Knowledge A Comprehension, 2 How to move from relational databases to Big data Synthesis, B Evaluation 3 Discuss about CAP theorem. Comprehension C

4 Discuss about Column databases. Knowledge D

5 Discuss with suitable examples about Document based databases Knowledge E

6 Discuss graph databases Comprehension E Comprehension, 7 Explain about MapReduce processing in analyzing data A Synthesis,

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Evaluation

8 Discuss in detail about simplest class of analytics Comprehension B

9 Discuss about outlier detection and elimination Comprehension C

10 Discuss in detail on data processing in analytics. Comprehension D

UNIT –IV Knowledge, 1 Describe machine learning algorithms Comprehension, A Evaluation Knowledge, Describe briefly about Train model using statistical/machine learning 2 Comprehension, B algorithms, Test model. Evaluation Knowledge, 3 Describe briefly about various algorithms used for prediction. Comprehension, C Evaluation Comprehension, 4 Explain about K Means analysis using R Tool. Synthesis, D Evaluation Knowledge, 5 Describe the analyzing process of sample set in R studio. Comprehension, E Evaluation UNIT –V Application, 1 Write down steps involved in Data Visualization InTableu. A Synthesis Application, 2 Write about role of Tableau in Data Visualization B Synthesis Application, 3 Write about role of qlickview in data visualization C Synthesis 4 List different approaches to Asset scoring models Knowledge D Knowledge, Describe about Classing Report, Variable Reduction report, Model 5 Comprehension, E statistics Evaluation Comprehension, 6 Explain about planning and estimation Synthesis, E Evaluation

PART C (CRITICAL THINKING QUESTIONS)

Blooms Course S. No Question Taxonomy Outcome Level UNIT –I

1 Take a sample data and design a data flow process for that data Comprehension A Application, 2 Take a sample data and upload it into cloud Amazon S3 B Synthesis Take a sample data and upload it into cloud and provide permissions Application, 3 C in Amazon S3 Synthesis UNIT -II List the advantages Hadoop can provide for big data over traditional 1 Knowledge A sytems

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2 What are the core components in Hadoop explain their work flow Knowledge B

3 List the ecosystem of spark and explain them Knowledge C

UNIT -III Compare the various strategies which organizations consider for Analysis , 1 B effective knowledge management Evaluation Analysis , 2 Compare the various databases for analytics D Evaluation 3 Discuss descriptive analytics in Bigdata analytics Comprehension E

UNIT –IV

1 Discuss the use of hypothesis testing in machine learning Comprehension B

2 Give an example algorithm for k means in machine learning Comprehension D

3 Sketch the importance of machine learning in analytics Understand E

4 Give example implementation and usage of Dash board in tableau Comprehension C

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13. SOFTWARE TESTING FUNDAMENTALS(A11210)

13.0 COURSE DESCRIPTION

Course Title Software Testing Fundamentals Course Code A11210 Regulation MLR-15 Lectures Tutorials Practical Credits Course Structure 3 2 - 3 Course Coordinator Mr. J Pradeep Kumar Team of Instructors Mr.K.Hemanath

13.1 COURSE OVERVIEW: This course is designed to enable a clear understanding and knowledge of the foundations, techniques, and tools in the area of software testing and its practice in the industry. The course sees that whether you are a developer or a tester, you must test software. This course is a unique opportunity to learn strengths and weaknesses of a variety of software testing techniques.

13.2 PREREQUISITES:

Level Credits Periods/Weeks Prerequisites UG 3 5 Software Testing Basics

13.3 A) MARKS DISTRIBUTION:

University End Session Marks Total Marks Exam Marks There shall be 2 Mid Term Examinations. Each Mid Term Examination consists of a Subjective Test and an Objective Test. The Subjective Test is for duration of 1.30 hr and the Objective Test is for duration of 30 minutes. The Objective Test consists of 10 multiple choice and 10 fill in the blanks type questions. The student has to answer all the questions and each question carries Half Mark. The subjective test is for 10 marks and the objective test will be for 10 marks. Subjective test in midterm examinations shall contain 6 questions, with each question having part a) and part b). Each question will carry 2 75 100 marks and the student needs to answer any 3 questions. First midterm examination shall be conducted for the first two and half units of syllabus and second midterm examination shall be conducted for the remaining two and half units. Five marks are earmarked for assignments. There shall be two assignments and the marks shall be awarded considering the best of two assignments in each course. Marks shall be awarded considering the best of two Mid Term Examinations in each course.

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13.4 EVALUATION SCHEME:

S. No Component Duration Marks 1 I Mid Examination 120 minutes 20 2 I Assignment - 5 3 II Mid Examination 120 minutes 20 4 II Assignment - 5 5 External Examination 3 hours 75

13.5 COURSE OBJECTIVES & OUTCOMES

Course Objectives Course Outcomes Blooms Level To study fundamental concepts in software I Have an ability to apply software testing testing, including software testing objectives, knowledge and engineering methods. process, criteria, strategies, and methods. BL 3, BL4

II To discuss various software testing issues Have an ability to design and conduct a software and solutions in software unit test; test process for a software testing project. BL 4, BL 5 integration, regression, and system testing.

III. To learn how to planning a test project, Have an ability to identify the needs of software design test cases and data, conduct testing test automation, and define and develop a test operations, manage software problems and tool to support test automation. BL 3, BL 6 defects, generate a testing report. IV. To expose the advanced software testing Have an ability understand and identify various topics, such as object-oriented software software testing problems, and solve these testing methods, and component-based problems by designing and selecting software BL 4, BL 5 software testing issues, challenges, and test models, criteria, strategies, and methods. solutions Have an ability to use various communication V. To gain software testing experience by methods and skills to communicate with their applying software testing knowledge and teammates to conduct their practice-oriented BL 5, BL 6 methods to practice-oriented software testing software testing projects. projects.

BLOOMS LEVEL (BL) BL 1: Remember / knowledge BL2: Understanding BL3: Apply

BL 4: Analyze BL 5: Evaluate BL 6: Create

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13.6 HOW PROGRAM OUTCOMES ARE ASSESSED:

Proficiency Program Outcomes Level Blooms Level assessed by An ability to apply the knowledge of mathematics, Computing, BL 3 Science and engineering to solve Computer Science and A Engineering N ------problems. An ability to design and conduct engineering experiments, as Assignments, BL 2 B well as to analyze and interpret data. H Tutorials An ability to design and construct a hardware and software BL 4 C system, component, or process to meet desired needs, within S Assignments, Tests realistic constraints. Graduates will demonstrate an ability to visualize and work on Assignments, BL 2 D laboratory and Multi-disciplinary tasks individually or as a H Tutorials, Exams member within the teams. An ability to demonstrate skills to use the techniques, modern BL 2 E engineering Tools, Software and equipments necessary to H Assignments, Tests analyze computer engineering Problems. An ability to recognize the global issues like green initiatives BL 4 G and alternate energy recognize the rural requirements. N -----

The broad education necessary to understand the impact of BL 5 H engineering solutions in a global, economic, environmental, N ------and societal context. Graduate will develop confidence for self education and Assignments, BL 6 acquire new knowledge in the computing discipline and ability H I and practice for Multi-disciplinary tasks as a member within Tutorials the teams To communicate effectively BL 3 J N ------An ability to use the techniques, skills and modern engineering Assignments, BL 6 K tools practice necessary for Engineering practice. S Tutorials Graduates are able to participate and succeed in competitive BL 5 L examination like GRE, GATE, TOEFL, GMAT etc N ------

The use of current application software and the design and use BL 4 ofoperating systems and the analysis, design, testing and Assignments, M H documentation of computer programs for the use computer Tutorials science and engineering technologies . N An ability to setup an enterprise. S Assignments BL 6 N = None S = Supportive H = Highly Related

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13.7 SYLLABUS:

Software Testing Fundamentals

Unit-I: Basics of software testing, Testing objectives, Principles of testing, Test Life Cycle, Types of testing, Software defect tracking.

Unit-II: White Box and Black Box Testing, White box testing, static testing, static analysis tools, Structural testing: Unit/Code functional ,testing, Code coverage testing, Code complexity testing, Black Box testing, Requirements based testing. Unit-III: Integration, System, and Acceptance Testing Top down and Bottom up integration, Functional versus Non-functional testing, Design/Architecture verification, Deployment testing, Beta testing, Scalability testing, Reliability testing, Stress testing, Acceptance testing

Unit-IV: Test Selection & Minimization for Regression Testing Regression testing, Regression test process, Initial Smoke or Sanity test, Selection of regression tests, Execution Trace, Dynamic Slicing, Test Minimization, Tools for regression testing, Ad hoc Testing: Pair testing, Exploratory testing, Iterative testing, Defect seeding.

Unit-V: Test Management and Automation Test Planning, Management, Execution and Reporting, Software Test Automation: Scope of automation, Design & Architecture for automation, Generic requirements for test tool framework, Test tool selection.

Text Books: 1. S. Desikan and G. Ramesh, “Software Testing: Principles and Practices”, Pearson Education. 2. Aditya P. Mathur, “Fundamentals of Software Testing”, Pearson Education. 3. Naik and Tripathy, “Software Testing and Quality Assurance”, Wiley 4. K. K. Aggarwal and Yogesh Singh, “Software Engineering”, New Age International Publication.

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13.8 COURSE PLAN:

Course Lecture Blooms Learning Topics to be covered Reference No. Level Outcomes 1 A Introduction to software testing T1 1,2 T1 2 A,b Basics of software testing 1,2

T1 3 A Testing objectives 1,2

T1 4 A,c Testing objectives 1,2,3

T1 5 A Principles of testing 1,2,3

T1 6 A Principles of testing 1,2

T1 1,2,3 7 B Test Life Cycle

T1 1,2,3 8 B Types of testing T1 1,2,3 9 B,c Types of testing T1 1,2,3 10 A,d Software defect tracking T1 11 A,d Software defect tracking 1,2,3,4,5,6 T1 12 A,d White box testing 1,2

T1 13 A,d,e static testing 1,2,3,4,5,6

T1 14 A,b,c static analysis tools 1,2

Structural testing: Unit/Code functional T1 15 A,d,e 1,2 testing, T1 16 A,e Code coverage testing 1,2,3

T1 17 B,d Code complexity testing 1,2 3 & 4

T1 18 A,d Black Box testing 1,2 3 & 4

T1 19 A, e 1,2 3 Requirements based testing T1 20 A,e Integration, System 1,2,3

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T1 21 D Testing Top down and Bottom up 1,2 integration T1 22 C,d Functional versus Non-functional testing 1,2,3,4

T1 23 A,d,e Design/Architecture verification 1,2,3,4

T1 24 A,e Deployment testing 1,2,3,4

T1 25 B,c Beta testing 1,2

T1 26 A,d Scalability testing 1,4,5

T1 27 A,e Reliability testing 1,2,3

T1 28 A,d Stress testing 5,6 T1 29 A,d Acceptance testing 1,3

Selection & Minimization for Regression T1 30 A,d 2,3 Testing T1 31 A,d Regression testing 1,4,6

T1 32 A,e Regression test process 1,2,3

T1 33 Ae Initial Smoke or Sanity test, 2,3

T1 34 D Selection of regression tests 1,2

T1 35 A,e Execution Trace, Dynamic Slicing 1,2,3,4,5,6

T1 36 B,c,e Test Minimization 1,2

T1 37 A,e Tools for regression testing, 1,2,3

T1 38 A,c,d,e Ad hoc Testing 1,2,3,4

T1 39 A,d,e Pair testing 1,2

T1 40 A,d Exploratory testing 2,3,4

T1 41 A,d,e Iterative testing 3,4,5 T1 42 A,d,e Defect seeding 1,2,3,6 T1 43 A,d,e Test Management 2,4,5

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T1 44 A,d Automation Test Planning 1,3,4

T1 45 A,d Management, 1,2,4,5 T1 46 A,d,e Execution and Reporting 1,2,3,4,5

Software Test Automation: Scope of T1 47 A,e 1,2,3,6 automation T1 48 A,b Design & Architecture for automation 1,2,3

Generic requirements for test tool T1 49 B,c 1,2 framework. T1 50 D,e Test tool selection 1,2,4

13.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES

Course Outcomes Course Objective A b C d e f I S II H III S H IV S V S H

S=Supportive H=Highly Related

13.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES

Course Name - Course Outcomes / Program Outcomes 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Software testing Fundamentals

Have an ability to apply software testing knowledge and engineering methods. 2 1 1

Have an ability to design and conduct a software test process for a software testing project. 3 2 3 1 2

Have an ability to identify the needs of software test automation, and define and develop a test tool to support 2 1 1 2 test automation.

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Course Name - Course Outcomes / Program Outcomes 1 2 3 4 5 6 7 8 9 10 11 12 13 14

Have an ability understand and identify various software testing problems, and solve these problems by designing and selecting software test models, criteria, strategies, and methods. 2 1 2 3 1 2 3

Have an ability to use various communication methods and skills to communicate with their teammates to conduct their practice-oriented software testing projects. 1 2 3 1 2 3

13.11 OBJECTIVE BITS

UNIT 1

1. Which of the following is NOT a white box technique? a) Statement testing b) Path testing c) State transition testing d) Data flow testing

Answer: C

2. Which of these activities provides the biggest potential cost saving from the use of CAST? a) Test management b) Test execution c) Test design d) Test planning

Ans: B

3. Which of the following would NOT normally form part of a test plan? a) Features to be tested b) Risks c) Incident reports d) Schedule

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Ans: C

4. According to phase 1 of testers mental life a)Testing shows software work b)Testing shows software doesn’t work c)Testing = debugging d)Testing is not an act

Ans: A

5. What is the main difference between a walkthrough and an inspection? a) A walkthrough is lead by the author, whilst an inspection is lead by a trained moderator. b) An inspection has a trained leader, whilst a walkthrough has no leader. c) Authors are not present during inspections, whilst they are during walkthroughs. d) An inspection is lead by the author, whilst a walkthrough is lead by a trained moderator.

Ans: A

6. Which of the following characterizes the cost of faults? a) They are easiest to find during system testing but the most expensive to fix then. b) They are cheapest to find in the early development phases and the most expensive to fix in the latest test phases. c) Faults are cheapest to find in the early development phases but the most expensive to fix then. d) Although faults are most expensive to find during early development phases, they are cheapest to fix then.

Ans: B

7. Integration testing in the small: a) Tests the individual components that have been developed. b) Only uses components that form part of the live system. c) Tests interactions between modules or subsystems. d) Tests interfaces to other systems.

Ans: C

8. In quantifying risk, the term RE represents ______

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A. Risk Expense

B. Related Expense

C. Risk Exposure

D. Risk Estimation

Ans: C

9.What is the primary objective of the system proposal from the producer's viewpoint?

A. To present the costs / benefits of the proposal

B. To obtain an agreement for more work

C. To standardize presentations

D. To present the methodology of operations

Ans: B

10.Syntax errors are a) data bugs b)logic bugs c)coding bugs d)Structuired bugs

Ans: C

11. Requirement Engineering is not concern with ______. a. Requirement Design b. Requirement Elicitation c. Requirement Analysis d. Requirement Documentation

Ans: A

12. Which Testing is performed first? a. Black box testing b. White box testing c. Dynamic testing d. Static testing

Ans: D

13. Verification and Validation uses ______.

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A. Internal and External resources respectively. b. Internal resources only. c. External resources only. d. External and Internal resources respectively.

Ans: A

14. This phase of the SDLC is known as the “ongoing phase” where the system is periodically evaluated and updated as needed. A. preliminary investigation B. system design C. system implementation D. system maintenance

Ans: A

15 ………. includes the existing system, the proposed system, system flow charts, modular design of the system, print layout charts and data file designs. A. Feasibility Report B. Functional Specification Report C. Design Specification Report D. Terms of Reference

Ans: C

16. After implementation of the system, system maintenance could be done for A. Minor changes in the processing logic B. Errors detected during the processing C. Revision of the formats of the reports D. All of the above

Ans: D

17. The final step of the system analysis phase in the SDLC is to A. gather data B. write system analysis report C. propose changes D. analyze data

Ans: B

18. The different phases for development and testing of the systems includes i) Development and testing of the individual programs ii) Development and testing of the system modules as a part of the major subsystems iii) Development and testing of the major subsystems as a part of the proposed system A. i and ii only

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B. ii and iii only C. i and iii only D. All i, ii and iii

Ans: D

19. A feasibility study is used to determine the proposed systems A. resource requirements B. costs and benefits C. availability of hardware and software D. all of the above

Ans: D

20 During which phase of the SDLC are users trained to use the new system? A. preliminary investigation B. systems implementation C. systems development D. systems maintenance

UNIT-2

1. A testing which checks the internal logic of the program is A. Black box testing B. White box testing C. Both (A) and (B) D. None of the above Ans: B

2. The Cyclomatic Complexity, V(G) was developed by A. Howard B. McCabe C. Boehm D. None of the above. Ans: B

3. A node with in degree � 0 and out degree = 0 is known as

A. Source node B. Destination node C. Predicate node D. None of the above Ans: B

4. A node with in degree = 0 and out degree � 0 is known as

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A. Source node B. Destination node C. Transfer node D. None of the above.

Ans: A

5. The Cyclomatic Complexity, V(G) is given by which formula

A. V(G) = e - n + 2

B. V(G) = e - 2n + P

C. V(G) = e - 2n

D. None of the above

Ans: A

6. A predicate node is the one, which has

A. Two outgoing edges

B. No outgoing edges

C. Three or more outgoing edges

D. None of the above

Ans: A

7. An independent path is the one

A. That is a complete path from source to destination node

B. That is a path which introduces at least one new set of processing statements

C. That is a path which introduces at most one new set of processing statements

D. None of the above

Ans: B

8. The size of the graph matrix is

A. Number of edges in the flow graph

B. V Number of nodes in the flow graph

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C. Number of paths in the flow graph

D. Number of independent paths.

Ans: B

9. In data flow testing, objective is to find

A. All dc-paths that are not du-paths

B. V All du-paths

C. All du-paths that are not dc-paths

D. All dc-paths

Ans: C

10. Who leads a walkthrough?

a. Author b. Moderator c. Reviewer d. Scribe

Ans: A

11. Which of the following is / are not an important goal of a walkthrough? a. Knowledge transfer b. Gather information c. Discuss alternatives d. Find defects

Ans: A

12. To check whether coding standards are followed, which type of testing will be beneficial? a. Dynamic Testing b. Static Testing c. Parameter Testing

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Ans: B

13. Which is not a type of Review?

a. Requirement Analysis b. Peer to peer c. Technical d. Walk through

Ans: A

14. Which are the benefits of Static Testing? a. Early feedback of a quality. b. Less rework cost. c. Increased developmental productivity. d. All of the above

Ans: D

15. Code coverage analysis is the process of

A) Finding areas of a program not exercised by a set of test cases, B) Creating additional test cases to increase coverage, and C) Determining a quantitative measure of code coverage, which is an indirect measure of quality. D) All of above.

Ans: D

16. IEEE 829 test plan documentation standard contains all of the following except a) Test items b) Test deliverables c) Test specifications d) Test tasks

Ans: C

17. When should testing be stopped? a) When all the planned tests have been run b) When all faults have been fixed correctly c) When time has run out d) It depends on the risks for the system being tested

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Ans: D

18. In which order should tests be run? a) The most important tests first b) The order they are thought of c) The easiest tests first(to give initial confidence) d) The most difficult tests first(to allow maximum time for fixing)

Ans: A

19. When should you stop testing? a) When time for testing has run out. b) When the test completion criteria have been met c) When all planned tests have been run d) When no faults have been found by the tests run

Ans: B

20. Which of the following is true? a) Component testing should be black box, system testing should be white box. b) The more tests you run, the more bugs you will find. c) The fewer bugs you find,the better your testing was d) If you find a lot of bugs in testing, you should not be very confident about the quality of software

Ans: D

UNIT 3 1.______is a unit of work seen from a system user's point of view. a)Transaction b)Transaction Flows c)Transaction flow graph d)none 2) Transaction begins with ______Transaction a)Birth b)Transaction c)flow graph d)Start 3) Expand MIMD a.Multiple Instruction Multiple Data b.Multiple Instruction Model Data c.Model Instruction Multiple Design d.Model Instruction Model Design 4) The predator process eats prey process in ______a.Adsorption

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Department of CSE b.Absorption c.Transaction d.Flow graph 5) C, P in case of data object state and usage are a) creation,participation b) creation,postulation c) calculation,predicate d) calculation,postulation 6. The statement that is true in case of transactional flow instrumentation is a) Dispatchers are needed b) Pay off is counters c) Counters are useful d) Counters are not useful 7.______are assumed problematic for software designers. a)births b) absorptions c) conjugations d)all the above 8. The methods of sensitization in transaction flows include a) using of patches b) use break points c) counters d) processing queue 9) ______is a natural agenda for system reviews, or inspections. a) Transaction b) Transaction Flows c) Transaction flow graph d) None 10) About ____ % of the effort of transaction flow test design, is the design and maintenance of the test databases. a.20% to 30% b.10% to 20% c.30% to 40% d.50% to 60% 11) ______is a model of the structure of the system's behavior. a) Flow chart b) Flow graph c) Transaction flow graph d) None of the above. 12) A parent process generates a daughter process, and both the processes continues. This situation is known as ______a) Decison b) Biosis c) Mitosis d) None of the above 13) A parent process generates two daughter processes, and only the daughter processes continues. This situation is known as ______a) Decison b) Biosis c) Mitosis

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Department of CSE d) None of the above 14) The opposite of Mitosis is ______a) Biosis b) Junction c) Absorption d) Conjugation. 15) How much % of transactions is to be covered in a walkthrough? a) 100% b) 98%-99% c) 80%-90% d) Around 75% 16) In a walkthrough, discuss the paths through the flows in ______terms. a) Functional b) Non technical c) technical d) semi technical 17) One should design more test cases to search for ______a) Lost daughters b) Illegitimate births c) Wrongful deaths d) All of the above. 18) Which of the following is problematic for software designer? a) Births b) Absorptions c) Conjugations d) All of the above 19) An airline reservation system has ______transaction flows. a) Tens of b) Hundreds of c) Thousands of d) None of the above. 20) About ____ % of the effort of transaction flow test design, is the design and maintenance of the test databases. a) 30% to 40% b) 40% to 50% c) 50% to 60% d) 60% to 70% UNIT IV 1. Using x+y>=10 when the correct equation is x+y>=5 is an example of a) Closure bug b) Titled bug c) Missing boundary 2) At least __% of the contemporary source code consists of data declaration statements. a) 20 b) 30 c) 40 d) 50 d) Shifted boundary 3) Processing components are generally cheaper than memory components. a) False.

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Department of CSE b) True 4) Most computers today are ______machines. a) Non Von Neumann b) Von Neumann c) MIMD d) XIMD 5) Data objects can be ______a) Created b) Killed c) Used d) All of the above 6) In a data flow graph, dd is probably harmless, but suspicious. A) True. B) False 7) In a data flow graph, dk is probably bug. A) True. B) False 8. If two distinct domains are overlapped, then they are said to be a) Ambiguous b) Over specified c) contradictory d) Unambiguous 9. Nice domains should not be a) Linear b) Simply connected c) Concave d) Complete 10. Domains are more useful in a) Interface testing b) System testing c) Unit testing d) Acceptance testing 11. Span is defined as a) largest value b) range of values c) smallest value d) middle value 12. The compatibility of callers range and called routines domain is confirmed by a) Testing all variables at a time b) Testing only one variable c) Not testing any variable d) Testing every input individually 13. A domain can be considered as a) Set b) Routine c) Boundary d) Congregation 14. The point that lies between two specific points of a domain is a) Off point b) On point

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Department of CSE c) Boundary point d) Extreme point 15) In a data flow graph, kd is normal case. A) True. B) False 16) In a data flow graph, ku is a bug. true/False? A) True. B) False 17. Domain testing is a form of a) Black box testing b) White box testing c) closed box testing d) None 18) Expand AD strategy. a) Any Design Strategy b) All Definitions strategy c) Any Data Flow Strategy d) All Designs Strategy 19) In a data flow graph,_d is normal case. True/False? A) True. B) False 20) In a data flow graph, k_ is normal case. True/False? A) True. B) False

UNIT V 1.aa*= a)a*a b) a+ c) a* d)Both (a) and (b) 2.Two successive path segment is expressed by concatenation is known as a)path product b)path expression c)Boolean algebra d)path sum 3.The first steps in node reduction is a)single link b)loop reduction c)Combine all serial links d)Combine all parallel links 4 The weight expression of serious path of A and B in lower path count arithmetic is a)Min(WA,WB) b)Max(WA,WB) c)sum(WA,WB) d)product(WA,WB) 5.If the probability of looping node is PL, probability of non looping operation a)1-PL b)1+PL c)1+1/PL

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Department of CSE d)PL+1/PL 6.data anomaly is represented using ______sequence a)three character sequence b)one character sequence c)four character sequence d)two character sequence 7.The main goal of reduction process is a)To retain only entry and exit nodes b) To retain only entry nodes c) To retain only exit nodes d) NONE OF THE ABOVE 8.The main step in achieving the node is a)Cross term b) Parallel term c) series term d) loop term 9.To remove elements from stack, the operation used is a)Pop b)delete c) push d)insert 10.If G is get operation then G + G would be a)G b) 0 c) 1 d) G+G 11. a ______flow graph is one that can be reduced to a single link a) structured b) unstructured c) control flow graph d)flow graph 12. ______theorm is useful in test design a)cook’s b)huangs c) parallel d)reduction 13.for a loop of mean N times looping probability is ______a) N+1 b)N-1 c)N/2 d) n/(n+1) 14.for a loop of mean N times not looping probability is ______a) 1/(n+1) b) 1/(n-1) c) n/n(n+1) d)n/n(n-1) 15.replacing link names with no. of paths is called ______a) annotations b)series loop c)parallel loop

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d) link 16.predator transaction consumes a prey this is called as ______a) au anomaly b) du paths c) anomaly d) none 17______are conducted at preliminary design level a) To retain only entry and exit nodes b) To retain entry nodes c) To retain onlty exit nodes d) Normal reduction 18.0transaction information is stored in ______a)loop b)path c)predicate d)path expression 19.______uses finite state machine to determine next process a) transaction dispatcher b) transaction flow c) mergers d) none 20.transaction control tables are used to perform______a) unit test b)component test c)self test d)both a and b

13.12 TUTORIAL QUESTIONS PART-A (SHORT ANSWER QUESTIONS)

Blooms S. Program Questions Taxonomy No Outcome Level UNIT-I 6. Explain goals of testing in software testing? Understand 1 7. What is verification and validation? Remembering 2 8. Explain software testing ? Remembering 2 UNIT II What is white box testing ? 6. Applying 3

Explain static testing and black box testing? 7. Analyzing 4 Describe structural testing? 8. Understand 1

What is code coverage testing? 9. Remembering 2

Explain state graph based testing? 10. Applying 3

11. Define boundary value analysis? Remembering 2 UNIT III

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6. Define integration system? Understand 1 7. Describe acceptance testing? Remembering 2 8. Explain top down and bottom up integration? Remembering 2 9. Define stress testing? Understand 1 UNIT IV 10. Define regression testing? Understand 2 11. Describe scalablity testing? Understand 1 12. Explain stress testing and acceptance testing? Applying 3

UNIT V 6. Describe test management and automation? Understand 1 Difference between test management and software test 7. Analyzing 4 automation 8. Define test planning Remembering 2 PART – B LONG ANSWER QUESTIONS

Blooms S. Program Questions Taxonomy No Outcome Level UNIT I 1 Explain basics of software testing? Understand 1 2 What are the principles of testing? Analyzing 4 Explain types of testing? 3 Applying 3

UNIT II 1. Difference between white box testing and black box testing? Applying 3 2. Explain static analysis tools? Understand 1 3. Explain state graph based testing? Evaluating 5 4. What are types of equivalence portioning? Evaluating 5 UNIT III 1. Difference between topdown and bottom up integration? Evaluating 5 2. Explain deployment testing ? Evaluating 5 3. Explain design/architecture verification? Understand 1 4. Explain beta testing,scalablity testing? Remembering 2

UNIT IV

1 Explain test selection&minimization for regression testing Understand 1 2 Describe adhoctesting and defect seeding Remembering 2 UNIT V 1 Explain test management and automation test planning Remembering 2 2 Describe test tool selection Evaluating 5 What are generic software automation 3 Applying 3

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13.13 ASSIGNMENT QUESTIONS PART-A (SHORT ANSWER QUESTIONS)

Blooms S. Program Questions Taxonomy No Outcome Level UNIT-I 1 Explain goals of testing in software testing? Understand 1 2 What is verification and validation? Remembering 2 3 Explain software testing? Remembering 2 UNIT II

What is white box testing? 1 Analyzing 4

Explain static testing and black box testing? 2 Understand 1

Describe structural testing? 3 Remembering 2

What is code coverage testing? 4 Applying 3

Explain state graph based testing? 5 Remembering 2

6 Define boundary value analysis? Applying 3 UNIT III 1 Define integration system? Understand 1 2 Describe acceptance testing? Remembering 2 3 Explain top down and bottom up integration? Remembering 2 4 Define stress testing? Understand 1 UNIT IV 1 Define regression testing? Understand 2 2 Describe scalability testing? Understand 1 3 Explain stress testing and acceptance testing? Applying 3 UNIT V Remembering 2 1 Describe test management and automation? Understand 1 Difference between test management and software test 2 Analyzing automation 3 Define test planning Remembering 2

PART – B LONG ANSWER QUESTIONS

Blooms S. Program Questions Taxonomy No Outcome Level UNIT I 1 Explain basics of software testing? Understand 1 2 What are the principles of testing? Analyzing 4 3 Explain types of testing? Applying 3

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UNIT II 5. Difference between white box testing and black box testing? Applying 3 6. Explain static analysis tools? Understand 1 7. Explain state graph based testing? Evaluating 5 8. What are types of equivalence portioning? Evaluating 5 9. Difference between white box testing and black box testing? Applying 3 UNIT III 5. Define integration system? Evaluating 5 6. Describe acceptance testing? Evaluating 5 7. Explain top down and bottom up integration? Understand 1 UNIT IV 1 Define regression testing? Understand 2 2 Describe scalability testing? Understand 1 UNIT V 1 Describe test management and automation? Remembering 2 Difference between test management and software 2 Evaluating 5 testing

PART – C (PROBLEM SOLVING AND CRITICAL THINKING QUESTIONS)

Blooms S. Program Questions Taxonomy No Outcome Level UNIT I 1. Explain goals of testing in software testing? Applying 3 2. What is verification and validation? Understand 1 UNIT II Explain static testing and black box testing? 1 Analyzing 4

Explain scalability testing and white box testing? 2 Evaluating 5

UNIT III 1 Describe scalability testing? Remembering 2 2 Explain stress testing and acceptance testing? Creating 6 UNIT IV 1 Describe scalability testing? Remembering 2 2 Explain stress testing and acceptance testing? Understand 1 UNIT V 1 Describe test management and automation? Evaluating 5 Difference between test management and software 2 Evaluating 5 testing

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14. CRYPTOGRAPHY AND NETWORK SECURITY(A10539)

14.0 COURSE DESCRIPTION

14.1 COURSE OVERVIEW: This course will emphasize on principles and practice of cryptography and network security: classical systems, symmetric block ciphers (DES, AES, other contemporary symmetric ciphers), linear and differential cryptanalysis, perfect secrecy, public-key cryptography algorithms for factoring and discrete logarithms, cryptographic protocols, hash functions, authentication, key management, key exchange, signature schemes, email and web security, viruses, firewalls, digital right management, and other topics. In this course students will learn as aspects of network security and cryptography.

14.2 PREREQUISITE(S):

Level Credits Periods / Week Prerequisites

UG 3 5 Basic Mathematics and Computation skills.

14.3 COURSE ASSESSMENT METHODS: c) Marks Distributions (Traditional Evaluation methods)

University Total Session Marks (25M) End Marks Exam Marks Mid Semester Test There shall be two midterm examinations. Each midterm examination consists of subjective type and objective type tests. The subjective test is for 10 marks of 60 minutes duration. Subjective test of shall contain 4 questions; the student has to answer 2 questions, each carrying 5 marks 75 100 The objective type test is for 10 marks of 20 minutes duration. It consists of 10 Multiple choice and 10 objective type questions, the student has to answer all the questions and each carries half mark. First midterm examination shall be conducted for the first two and half units of syllabus and second midterm MLR Institute of Technology, Dundigal, Hyd-500043 Page 139

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examination shall be conducted for the remaining portion.

d) Expected Learning Outcomes and Methods for Assessing S. Expected Learning Outcomes Assessment method (s) No Ability to Identify basic security attacks A Quiz on security attacks and services. and services Case studies on symmetric and Ability to learn symmetric and asymmetric B asymmetric key algorithms for key algorithms for cryptography cryptography Case studies on Key Management Construct Key Management techniques C techniques and importance of number and importance of number Theory Theory Group Activity/ solve various To solve Authentication functions the Authentication functions the manner in D manner in which Message Authentication which Message Authentication Codes Codes and Hash Functions works and Hash Functions works. Ability to examine the issues and structure Case study group wise activity / model of Authentication Service and Electronic design on examine the issues and E Mail Security structure of Authentication Service and Electronic Mail Security 14.4 EVALUATION SCHEME: S. No Component Duration Marks 1 I mid 80 M 20 2 I assignment - 05 3 II mid 80 M 20 4 II assignment - 05 5 External examination 3 Hours 75

14.5. COURSE OBJECTIVES AND COURSE OUTCOMES Course Outcomes Course Objectives Blooms Level At the end of the course V. To provide deeper understanding into cryptography, its application a. Students able to Identify basic to network security, BL 1 & 2 security attacks and services threats/vulnerabilities to networks and countermeasures. VI. To explain various b. Students able to Use symmetric approaches to Encryption and asymmetric key algorithms for techniques, strengths of Traffic BL 3,4 Confidentiality, Message cryptography and Design a security Authentication Codes. solution for a given application c. Students able to develop Analyze

Key Management techniques and

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importance of number Theory. VII. To familiarize Digital Signature d. Students able to develop Standard and provide solutions Authentication functions the manner BL 3,4 & 5 for their issues. in which Message Authentication Codes and Hash Functions works. VIII. To familiarize with e. Students will be able to examine cryptographic techniques for secure (confidential) the issues and structure of communication of two parties BL 4,5 & 6 Authentication Service and Electronic over an insecure (public) channel; verification of the authenticity of Mail Security the source of a message. BLOOMS LEVEL (BL) BL 1: Remember / knowledge BL2: Understanding BL3: Apply BL 4: Analyze BL 5: Evaluate BL 6: Create

14.6 HOW COURSE OUTCOMES ARE ASSESSED:

Department of CSE

Graduate will develop confidence for self education and acquire new knowledge in the computing discipline and Class Test & Analyze I S ability and practice for Multidisciplinary tasks as a Seminars member within the teams

N= None S= Supportive H = Highly Related

14.7 SYLLABUS

UNIT - III PUBLIC KEY CRYPTOGRAPHY AND RSA: Principles Public key crypto Systems, Diffie Hellman Key Exchange, the RSA algorithm, Key Management, , Elliptic Curve Arithmetic, Elliptic Curve Cryptography. MESSAGE AUTHENTICATION AND HASH FUNCTIONS: Authentication Requirement, Authentication Function, Message Authentication Code, Hash Function, Security of Hash Function and MACs. HASH AND MAC ALGORITHM: Secure

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Hash Algorithm, Whirlpool, HMAC, CMAC. DIGITAL SIGNATURE: Digital Signature, Authentication Protocol, Digital Signature Standard.

14.8 COURSE PLAN:

Course Blooms Levels Lecture Learning Topic Reference No. Outcomes Explain the objectives and Understanding / L1 functionality of Security Comprehension T1:1.1-1.5 A trends, Describe about the OSI Creating / Synthesis Security Architecture how T1:1.9-1.10 L2 cryptography and network T2: 1.2 A security have evolved Explain the Security Attacks Understanding / T1:1.4, 1.6- , Security Services of Comprehension 1.8, 2.1- L3 cryptography and network 2.3 A,B security. Explain the concepts of Understanding / T1 :2.5,2.6 L4 A Security Mechanisms Comprehension R1: 1.6 Explain the importance of A Understanding / L5 T2:2.5 A model for Network security. Comprehension L6 A Explain the Symmetric Understanding / T1:3.1

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Cipher Modes. Comprehension T2: 3.1-3.2 Understanding / T1:3.1, Explain the Substitute L7 Comprehension 4.1-4.5 Techniques B T2: 3.3, T2: 4 Understanding / T1:5.1-5.2 Describe Transposition L8 Comprehension T2: 9 Techniques. B R1- 2.4 Creating / Synthesis T1:5.3 Compare the performance of L9 T2- 9.2 the Rotor Machines B,C R1- 2.4 Understanding / T1:5.4 Explain about the L10 Comprehension T2: 10.3-10.6 Stenography A,D R1- 2.4 Creating / Synthesis T1:5.4 Discuss Block Cipher L11 R1- 2.4.4 Principles. A,D T2:10.2 Discuss the importance of Creating / Synthesis T1:5.5 L12 D Data Encryption Standards R1- 2.4.6 Explain the Creating / Synthesis T1:6.1-6.2 L13 A,D,E Strength of DES R1: 2.3 Describe reasons for using Creating / Synthesis T1:6.3-6.4 L14 Differential and Linear R1:2.3 A,B Crypt Analysis Explain the importance of Understanding / T1:6.5-6.7 L15 Block Cipher Design Comprehension R1: 2.3 A,B Principles Explain about Evaluation Understanding / T1:8.1 -8.3 L16 A,B Criteria for AES Comprehension R1: 3 Understanding / T1:8.4-8.6 L17 Explain the AES Cipher. A,B,C Comprehension R1: 3.3 Summarize the Multiple Understanding / T1:9.1- L18 B,D Encryption Comprehension 9.2R1:3.3 Creating / Synthesis T1:9.4 L19 Describe Triple DES A,C R1: 3.4 Explain Block Cipher Modes Understanding / L20 T1: 9.5-9.6 A,E of Operation. Comprehension Summarize the Stream Understanding / T1:10.1-10.3 L21 C,D Cipher and RC4. Comprehension R1: 4.1- 4.2 Explain about Prime Understanding / T1:10.4-10.6 L22 C,D Numbers. Comprehension R1: 4.1- 4.2 Describe a Fermat‘s and Creating / Synthesis T1:11.1-11.2 L23 A,D,E Euler‘s Theorem R1: 4.3 Describe Testing for Creating / Synthesis L24 T1: 11.3-11.4 A,E Primality. Summarize The Chinese Understanding / T1:11.5-11.6 L25 B,C Remainder Theorem Comprehension R1: 4.4 Analyze the various Discrete Understanding / L26 T1: 12.1 A,D,E logarithms Comprehension T1:12.2-12.3 L27 A,E Discuss about the Principles Creating / Synthesis

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Public key crypto Systems Describe Diffie Hellman Creating / Synthesis T1:12.4 L28 A,D Key Exchange R1: 5.4 Creating / Synthesis T1:12.5-12.6 L29 Discuss the RSA algorithm. A,D R1:5.4 Understanding / T1:7.1-7.3 L30 Explain Key Management A,E Comprehension R1: 6.2 Understand Elliptic Curve Understanding / T1: 7.4 L31 A,E Arithmetic Comprehension R1: 6.6 Understand Elliptic Curve Understanding / T1:7.5 L32 A,E Cryptography Comprehension R1: 6.5 Understand Authentication Understanding / T1:7.6-7.7 L33 E Requirement Comprehension R1: 6.4 Compare and contrast Understanding / L34 T1:14.1 E Authentication Function Comprehension Describe the Message Creating / Synthesis L35 T1:14.4-14.7 B,C,E Authentication Code Describe Hash Function, Creating / Synthesis L36 Security of Hash Function T1:14.8-14.9 A,E and MACs Explain the objectives of Understanding / T1:11.5-11.6 L37 A,B,C Secure Hash Algorithm Comprehension R1: 4.4 Describe about the Understanding / T1: 12.1 L38 B,D Whirlpool, HMAC. Comprehension T1:12.2-12.3 Understanding / L39 Explain the CMAC A,C Comprehension Explain the concepts of Creating / Synthesis T1:12.4 L40 A,E Kerberos R1: 5.4 Explain the X.509 Understanding / T1:12.5-12.6 L41 C,D Authentication Service Comprehension R1:5.4 Explain the Public Key Understanding / T1:7.1-7.3 L42 C,D Infrastructure Comprehension R1: 6.2 Explain the Pretty Good Understanding / T1: 7.4 L43 A,D,E Privacy (PGP). Comprehension R1: 6.6 Creating / Synthesis T1:7.5 L44 Describe S/MIME A,E R1: 6.5 Compare the Overview, IP Creating / Synthesis T1:7.6-7.7 L45 B,C Security Architecture R1: 6.4 Explain about the Understanding / L46 T1:14.1 A,D,E Authentication Header Comprehension Discuss Encapsulating Understanding / L47 T1:14.4-14.7 A,E Security Payload Comprehension Discuss the importance of Creating / Synthesis L48 Combining Security T1:14.8-14.9 A,D Associations Explain the Understanding / T1:11.5-11.6 L49 A,D Key Management Comprehension R1: 4.4 Describe reasons for Secure Understanding / T1: 12.1 L50 A,E Socket Layer (SSL) Comprehension T1:12.2-12.3

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Explain the importance of Understanding / T1: 12.1 L51 Transport Layer Security Comprehension T1:12.2-12.3 A,E (TLS) Explain about Secure Creating / Synthesis T1:12.4 L52 Electronic Transaction R1: 5.4 A,E (SET) Explain the Intruders, Understanding / T1:11.5-11.6 L53 E Viruses related threats Comprehension R1: 4.4 Summarize the Firewall Understanding / T1: 12.1 L54 A,B,C Design principles Comprehension T1:12.2-12.3 Understanding / T1: 12.1 L55 Explain Trusted Systems. A,C Comprehension T1:12.2-12.3

14.9 MAPPING COURSE OBJECTIVES LEADING TO THE ACHIEVEMENT OF COURSE OUTCOMES:

Course Outcomes Course Objective A B C D E I S S II S H H III H IV S H S

S=Supportive H=Highly Related

14.10 MAPPING COURSE OUTCOMES LEADING TO THE ACHIEVEMENT OF PROGRAM OUTCOMES:

Course Program Outcomes Educational A B C D E F G H I J K L M N Outcomes f. S S S H g. H H S H H H h. S H H H H i. S S H S S S j. S H S

S=Supportive H=Highly Related

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14.11 OBJECTIVE QUESTIONS:

2. Passive attack is A. Replay B. masquerade C. traffic analysis D. none of these Answer: C 3. is responsible for technical management of IETF activities and internet standard process.

A. IESG B. IETF C. IAB D. rfc publication Answer: B

4. Fabrication is attack on A. Confidentiality B. Non-repudiation C. Authentication D. Availability Answer: C 5. In phase system is continuously improved bugs are eradicated and features that that did not make an earlier release are added. A. inception B. elaboration C. construction D. transition Answer: D

6. Man in middle attacks leads to A. HTTP session hijack D. FTP session hijack E. TCP session hijack F. UDP session hijack Answer: D

7. Security service , requires that neither the sender nor the receiver of a message be able to deny the transmission.

A. NonRepudiation B. Availability C. Authentication D. Confidentiality Answer: C

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8. Security service , requires that neither the sender nor the receiver of a message be able to deny the transmission. A. NonRepudiation B. Availability C. Authentication D. Confidentiality Answer: A

9. Hijacking HTTP session involves obtaining A. The URL B. Session ID E. IP address F. Mac Address Answer: B

11. How many types cipher block modes of operations A. 4 B. 5 C. 6 D. 3 Answer: D

11. The key length of 3DES algorithm is A. 56 B. 168 C. variable D. 128 Answer: B

12. In DES algorithm the mathematical function used is A. Addition B. Subtraction C. Inclusive OR D. Exclusive OR Answer: B

13. The number of rounds in AES is A. 16 B. 10 C. 15 D. 9 Answer: B

14. Message Authentication Code is calculated as a function of A. Key B. Message C. Arbitrary number D. Message, key Answer: D

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15. treats digrams in the plaintext as single units and translates these units into cipher text digrams A. Substitution Cipher B. Playfair cipher C. Monoalphabetic cipher D. Hill Cipher Answer: B

16. For a given message, it is feasible to find y # x such that H(x) = H(y) is called as A. Two – way encryption B. Strong collision C. One – way encryption D. Weak collision

Answer: D

17. Hijacking HTTP session involves obtaining A. The URL B. Session ID C. IP address D. Mac Address Answer: B

18. Interruption attacks are also called attacks A. Masquerade B. Alteration C. Denial of service D. Replay attacks Answer: A

19. DOS attacks are cause by A. Authentication B.Alteration C.Fabrication D. Replay attacks Answer: D

21. replicates itself by creating its own copies, in order to bring the network to a halt. A. Virus B. Worm C. Trojan horse D. Bomb Answer: A

21. Virus is a Computer A. File B. Program C. Database D. Network Answer: B MLR Institute of Technology, Dundigal, Hyd-500043 Page 149

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UNIT-II

1. scrambled message produce as output.

E. plain text F. secret key G. cipher text H. encryption Answer: A

2. is the process of attempting to discover the plain text or key.

D. cryptography E. cryptanalysis F. cipher text D. stream cipher Answer: B

3. The most widely used public-key algorithms are types.

E) 1 F) 2 G) 3 H) 4 Answer: B

4. Same key is used for encryption and decryption

E) Symmetric/Conventional encryption F) Public-key cryptography G) Both H) None Answer: A

5. RSA is

E) Rivest, Shyam, Adleman F) Ricest, Shamir, Alice G) Rivest, Shamir, Adleman H) None Answer: A

6. RSA Algorithm cipher text is

E) C=M^e(mod n) F) C=E^M(mode n) G) Both H) None Answer: A

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7. Key exchange is big problem

E) Encryption F) Decryption G) Conventional encryption H) Public-key cryptography Answer: C

8. Diffie-Hellman key algorithm public keys Ya=?

E. Ya=Xa mod q F. Yb=Xb mod q G. both H. None Answer: A

9. Diffie –Hellman key exchange algorithm cab be used only for E. Encryption F. Decryption G. Key management H. None Answer: C 10 Diffie-Hallman algorithm public key Yb=?

E. Ya=Xa mod q F. Yb=Xb mod q G. both H. None Answer: B

11 Diffie-Hallman algorithm secret key K by user A=?

E. K=Xa mod q F. K=Xa mod q G. K=(Yb)^ Xa mod q H. All Answer: A

12 Diffie- Hallman algorithm secret key K by user B=?

E. K=(Ya)^ Xb mod q F. K=Xb mod q G. Both H. None Answer: B

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13 DSS is

E. Digital System Standard F. Digital Signature Standard G. Digital Signature System H. All the above Answer: B

14 Kerberos is a protocol

E. Confidentiality F. Integrity G. Authentication H. All Answer: A

15 TGS is

E. Ticket Granting Service F. Ticket Granting Server G. Both H. None Answer: A 16 The general schemes for digital signatures are

E. Direct F. Arbitrated G. Both H. None Answer: C

17 Major issues of key management are

E. Key life time F. Key size G. Key exposure H. Both a,c Answer: D

18 Management and handling of the pieces of Secret information is generally referred to as

E. Key management F. DSS G. Digital Certificate H. None Answer: A

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19 To establish identies , encrypt information and digitally sign document

E. CA F. DSS G. PKI H. None Answer: D

20 In Greek mythlogy Kerberos is

E. Authentication F. Security G. Dog H. Multithreaded dog Answer: D

UNIT – III

1. Which of the following documents provides the description of a packet authentication extension to IPv4 and IPv6

E. RFC 2401 F. RFC 2402 G. RFC 2406 H. RFC 2408 Answer: D 2. Which of the following documents provides the description of a packet encryption extension to IPv4 and IPv6 E. RFC 2401 F. RFC 2402 G. RFC 2406 H. RFC 2408 Answer: D

3. Which among the following Routing Protocols is used by IP Security

E. OSPF F. OPSF G. UDP H. TCP Answer: C

4. The attack in which intruders create packets with false IP addresses and exploit applications that use authentication based on IP address is called

E. Packet sniffing F. IP Spoofing G. Eaves dropping H. Modification Answer: D

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5. A process by which packets from one network are broken into smaller pieces to be transmitted on another network is know as

E. segmentation F. bifurcation G. fragmentation H. segregation Answer: C

6. Which of the following documents provides an overview of security architecture

E. RFC 2401 F. RFC 2402 G. RFC 2406 H. RFC 2408 Answer: D

7. Which of the following documents provides Specification of key management capabilities.

E. RFC 2401 F. RFC 2402 G. RFC 2406 H. RFC 2408 Answer: D

8. Which of the following algorithms are used by IPSec to provide per- packet authentication and data integrity E. HMAC MD5 F. 3DES G. AES H. Digital signature s, based on RSA and DSA Answer: D

9. Which among the following is carried in AH and ESP headers to e the receiving system to select the Security associations under whic received packet will be processed

E. Security Paramete rs index F. Security Protocol identifier G. IP destination address H. Network address Answer: A

10. Masquerade is an attack on

E. Data retrieval F. Authentication G. Nonrepudiation H. Data access Answer: D

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11. IPSec is provided at the layer

E. Below transport Layer F. Below network layer G. At the application layer H. At the physical Answer: D

12. Which among the following indicates whether the security association is an AH or ESP security association.

E. Security Parameters index F. Security Protocol identifier G. IP destination on address H. Network Address Answer: D

13. Which among the following mechanisms assures the receiver that the received packet was transmitted by authorized person

E. Confidentiality F. Nonrepudiation. G. Authentication H. key management Answer: C

14. Which among the following mechanisms assures the receiver that the messages are received as sent,with no duplication, insertion, modification, reordering or replays.

E. Confiden tiality F. Nonrepudiation G. Authenti cation H. Integrit y Answer: A

15. Which among the following mechanisms prevents either sender or receiver from denying a transmitted message

E. Confidentiality F. Nonrepudiation G. Authenti cation H. Integrity Answer: D

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16. For transport mode AH using IPv4, where is AH inserted

E. After original IPheader & before IP payload F. Before original IP header & before IP payload G. Before original IP header & After IP payload H. After original IP header & after IP payload Answer: A

E. Fault management F. Performance management G. Layer management H. Network management Answer: D

18. In relation to SNMP which of the following is defined by the ongoing adjustment to host and device configurations in a network without taking element out of service

E. Fault management F. Performance management G. Layer management H. Network management Answer: D

19. Which is a string of numbers, with each number representing a level in a hierarchical tree

D. MIB E. Trap F. OID D. SMI Answer: A

20. In relation to SNMP which of the following is defined by any network element that may be written to or read from, by a network manager

E. Managed object F. Network Object G. Routed object H. Managed subject Answer: D

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UNIT – IV

E. True positive F. False positive G. True negative H. False negative Answer: A

2 Which of the following apply to network-based IDS?

E. Provides reliable, real-time intrusion data F. Remains active and transparent on the network G. Uses many network or host resources H. Becomes active when identifying intrusions Answer: C

3 Which of the following intrusion detection systems functions in current or real time to monitor network traffic?

E. Network based F. Host based G. Gateway based H. Router based Answer: A

4 Which of the following describes how a network-based IDS acquires data?

E. Passive F. Active G. Very quiet H. Very noisy Answer: A

5 What does active detection refer to when using an intrusion detection system (IDS)? E. An IDS that is constantly running 24 hours a day F. An IDS that responds to the suspicious activity by logging off a user G. An IDS that simply detects the potential security breach H. An IDS that shuts down the Internet after a suspected attack Answer: B

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6 Which among the following is not a password selection strategy

E. User education F. Computer-generated passwords G. Stego password checking H. Proactive password checking Answer: C

7 In which among the following strategies a system periodically runs its own password cracker to find guessable passwords.

E. Proactive password checking F. Reactive password checking G. Active password checking H. Underactive password checking Answer: B

8 In which of the following schemes the system checks to see if a password selected by a user is allowable and, if not rejects it.

E. Proactive password checker F. Reactive password checker G. Active password checker H. Under active password checker Answer: A

9 Threshold detection comes under which of the following

E. Statistical anomaly detection system F. Rule-based detection system G. Time stamp method H. Detection specific password scheme Answer: B

10 Which of the following is most useful when detecting network intrusions?

E. Audit policies F. Audit trails G. Access control policies H. Audit practices Answer: B

11 SOCKS service is located on

C. TCP port 1080 D. TCP port 1088 E. TCP port 1081 F. TCP port 1082 Answer: A

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12 Version 5 of SOCKS is defined in

E. RFC 1892 F. RFC 1928 G. RFC 1298 H. RFC 1289 Answer: B

13 Which among the following is typically set up as a list of rules based on matches to fields in the IP or TCP header

E. Packet filters F. Application level gateways G. Circuit level gateways H. Session gateway Answer: C

14 Discarding all packets containing the route information that the packet should take as it crosses the internet router is which attack

E. Source routing attack F. IP address spoofing G. any fragment attack H. IP sniffing Answer: A

15 SOCKS server runs on which of the following platform based firewalls

E. UNIX F. Windows G. DOS H. JAVA Answer: A

16 Which among the following is not a firewall

E. Packet Filters F. Application level gateways G. Circuit level gateways H. Session gateway Answer: D

17 Which among the following are default policies of a packet filtering router

E. discard, forward F. discard, retrieve G. delete, forward H. delete, retrieve Answer: A

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18 Discarding packets with an inside source address if the packet arrived on an external interface is a counter measure to which of the following attacks

E. IP address spoofing F. Source routing attack G. Tiny fragment attack H. IP sniffing Answer: D

19 Which of the following is also called a proxy server

E. packet filter F. application level gateway G. circuit level gateways H. session gateway Answer: B

20 which among the following is a system identified by the firewall administration as a critical strong point in the networks security

E. Base host F. Bastion host G. Borland host H. Prime host Answer: DS UNIT - V. 1. One of the problems with using SET protocol is

E. The merchants risk is high as he accepts encrypted credit card F. The credit card company should check digital signature G. The bank has to keep a database of the public keys of all customers H. The bank has to keep a database of digital signatures of all customers Answer: B

2. The bank has to have the public keys of all customers in SET protocol as it has to

E. Check the digital signature of customers F. Communicate with merchants G. Communicate with merchants credit card Company H. Certify their keys Answer: C

3. Which among the following SET transactions indicates that a responder rejects a message because it fails format or content verification tests

A. batch administration

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E. certificate inquiry and status F. credit G. error message Answer: A

4. Which of the following SET transactions allows a merchant to communicate information to the payment gateway regarding merchant batches

E. batch registration F. batch administration G. batch processing H. batch authorization Answer: D

5. Which of the following SET transactions allows a merchant to correct a previously request credit

E. payment capture F. capture reversal G. credit reversal H. purchase request Answer: A

6. The Secure Electronic Transaction protocol is used for

A. credit card payment B.cheque payment C.electronic cash payments D. payment of small amounts for internet services Answer: A

7. In SET protocol a customer encrypts credit card number using

E. his private key F. bank's public key G. bank's private key H. merchant's public key Answer: B

8. In SET protocol a customer sends a purchase order E. encrypted with his public key F. in plain text form G. encrypted using Bank's H. public key using digital Signature system Answer: C

9. Which among the following SET transactions allows the merchant to request payment from the payment gateway

A. payment capture B.capture reversal C.credit reversal

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D. purchase request Answer: A

10. Which among the following SET transactions allows a merchant to correct a previously request credit

E. payment capture F. capture reversal G. credit reversal H. purchase request Answer: B

11. Alert that indicates an inappropriate message was received as defined in the SSL specification is

E. bad _record _mac F. unexpected _message G. illegal _ parameter H. unsupported message Answer: D

12. Select which reasons secure electronic transaction ( SET) is preferred to SSL

E. the vendor can verify the address of the purchaser F. the person making the payment is the legitimate card holder G. the purchaser may verify that the vendor is authorized to engage in payment card transaction H. guarantees delivery of goods or services Answer: B

13. Which among the SSL specific protocols that use SSL record protocol is the simplest

E. change cipher spec protocol F. TCP G. IP H. Handshake protocol Answer: D

14. Which of the following is not a SSL handshake protocol message type E. Server _hello F. Server _hello G. client _hello H. client _hello Answer: B

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15. SSL is implemented over which layer E. TCP F. IP G. HTTP H. FTP Answer: A

16. The handshake protocol, the change cipher spec protocol and the alert protocol are defined as part of which of the following protocols

E. HTTP F. IP G. TCP H. SSL Answer: D

17. SSL sessions are created by which of the following

E. Cipher spec protocol F. TCP G. IP H. Handshake protocol Answer: D

18. A session state from SSL specification is not defined by which of the following parameters

E. Server write MAC secret F. Session identifier G. Master secret H. Peer certificate Answer: B

19. connection state from SSL specification is not defined by which of the following parameters

E. Client write MAC secret F. Server write key G. Client write key H. Session identifier Answer: B

22. Which is not a SSL record protocol operation

E. Adding MAC F. Compression G. Encryption H. Expansion Answer: D

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14.12 TUTORIAL QUESTIONS PART-A (SHORT ANSWER QUESTIONS)

S.No Questions Blooms Course Taxonomy Outcome level UNIT-I 1 State the need for security Remember 1 2 Define Confidentiality Remember 1 3 Explain why are some attacks called as passive? Understand 3 4 State what is Plain Text and Cipher Text Understand 5 5 State what is encryption and decryption Understand 1 UNIT- II 1 Asses the reason to study Feistal Cipher create 6 2 State the problems with Symmetric key Encryption Remember 1 3 Differentiate between diffusion and confusion Analyze 4 4 State the purpose of using S-boxes in DES Remember 1 5 Differentiate between linear and Analyze 4 differential cryptanalysis UNIT- III 1 Compare the types of attacks are addressed by evaluate message authentication 5 2 Define is message authentication code Remember 1 3 Solve the problem Kerberos is designed to address analyze 3 4 List three approaches to secure user Remember 1 authentication in a distributed environment 5 Asses the purpose of x.509 standard create 6 UNIT- IV 1 State what is S/MIME? Remember 1 2 Discuss where do you apply PGP? Understand 1 3 Discribe some functions of PGP. Remember 1 4 List the S/MIME Functions. Remember 1 5 Explain the methods for protecting the password file. Understand 1 UNIT- V 1 List services provided by SSL or TLS Remember 1 2 Describe how master secret is created from Understand 1 premaster secret in SSL 3 Describe how key materials are created from Understand 1 master secret in TLS 4 Define the goal of each phase in the Handshake Remember 1 protocol 5 Describe the role of compression in the Understand 1 operation of a virus

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14.13ASSIGNMENT QUESTIONS PART A(SHORT ANSWER QUESTIONS)

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14.14TUTORIAL QUESTION BANK (5/UNIT) PART A (SHORT ANSWER QUESTIONS) S.No Questions Blooms Course Taxonomy Outcome level UNIT-I 1 Explain the two basic ways of transforming plain text to cipher text. Understand 1 2 Differentiate between substitution cipher and transposition cipher Analyze 4 3 Differentiate between a mono alphabetic cipher and poly alphabetic cipher? Analyze 4 4 Explain Steganography Understand 1 5 Explain the basic functions used in encryption Understand 1 algorithms? UNIT- II 1 Substitute Bytes Transformation create 6 2 What is the role of S-Box in DES? Remember 1 3 Discuss the design principles of block cipher technique? Analyze 4 4 What is a Feistel Cipher? Remember 1 5 Give the structure of AES. Analyze 4 UNIT- III 1 What are the requirements of cryptographic hash evaluate functions?. 5 2 What are the attacks that are possible on RSA? Remember 1 3 What are the requirements of Kerberos? analyze 3 4 Define MAC (Message Authentication Code). Remember 1 5 Write short notes on Digital Signature Algorithm create 6 UNIT- IV 1 What is meant by IP Spoofing? Remember 1 2 What is S/MIME? Understand 1 3 What are the keys used by PGP? Remember 1 4 What is e-mail security? Explain the technique for e- Remember 1 mail security? 5 What is the role of Key Distribution centre? Understand 1 UNIT- V 1 What is inter function call? Remember 1 2 What are the different combinations of Security Understand 1 Association on a network? 3 What are the contents of a Security Association? Understand 1 4 Sketch neatly the SSL protocol stack. Remember 1 5 What are the basic approaches of building Security Understand 1 Associations?

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14.15TUTORIAL QUESTION BANK (5/UNIT) PART A (LONG ANSWER QUESTIONS)

Questions Blooms Course S.No Taxonomy level Outcome UNIT-I Determine the security mechanisms required to Remember 1 1 provide various types of security services. Write briefly the categories of attacks. What are the 2 Remember 1 x.800 listed attacks? 3 What are the different transposition techniques? Explain Understand 3 4 Explain Hill cipher with an example. Understand 5 5 Explain Network security model with neat diagram. Understand 1 UNIT- II 1 Explain in detail about the steps involved in DES. create 6 How do you convert a block cipher into a stream 2 cipher by using the Cipher Feedback (CFB) mode? Remember 1 Explain. What are the various block cipher design principles? 3 Explain how different cryptographic algorithms use Analyze 4 Fiestel Cipher Structure? Which four tasks are performed in each round of 4 Remember 1 AES Cipher? Explain. Define OFB and list its advantages and 5 Analyze 4 disadvantages UNIT- III What is the cipher text if the plain text is 63 and 1 evaluate public key is 13? Use RSA algorithm. 5 Briefly explain the Diffie Hellman Key Exchange 2 Remember algorithm? 1 Give the structure of HMAC. Explain the applications of 3 analyze HMAC. 3 What are discrete logarithms? Explain how are they 4 Remember used in Public Key Cryptography? 1 Give the structure of SHA-512 compression 5 function. Explain the structure of each round. Is Man create 6 in the Middle attack possible on SHA-512 UNIT- IV Give the summary of cryptographic algorithms used by Remember 1 S/MIME 1 Describe the process involved in digital signatures. 2 Understand Explain about different digital signatures. 1 3 What are the main features of Kerberos Version 5? Remember 1 4 Explain about Pretty Good Privacy (PGP). Remember 1 5 Describe the architecture of IPSec. Understand 1 UNIT- V Explain the methods used for statistical anomaly 1 Remember detection. 1 2 Write briefly about the signature based Intrusion Understand 1

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Detection Systems. 3 Explain about SSL Handshake protocol. Understand 1 What is an audit record? What is the use of audit record in 4 Remember intrusion detection? 1 What are the different combinations of Security 5 Understand 1 Association on a network?

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15. CRYPTOGRAPHY AND NETWORK SECURITY LAB(A10549)

15.0 SYLLABUS

1. Breaking the Shift Cipher. 2. Breaking the Mono-alphabetic Substitution Cipher. 3. Implement RSA algorithm for encryption and decryption in ‘C’ 4. Message Authentication Codes 5. Cryptographic Hash Functions and Applications 6. Symmetric Key Encryption standards (DES) 7. Symmetric Key Encryption standards (AES) 8. Diffie-Hellman Key Establishment 9. Public-Key cryptosystems (PKCSv1.5) 10. Digital Signatures 11. Configure a mail agent to support Digital Certificates, send a mail and verify the correctness of this system using the configured parameters. 12. Configure SSH (Secure Shell) and send/receive a file on this connection to verify the correctness of this system using the configured parameters. 13. Configure a firewall to block the following for 5 minutes and verify the correctness of this system 15.1 LAB SCHEDULE

S.NO LAB Experiment Schedule data 1 Breaking the Shift Cipher. 2 Breaking the Mono-alphabetic Substitution Cipher. 3 Implement RSA algorithm for encryption and decryption in ‘C’ 4 Message Authentication Codes 5 Cryptographic Hash Functions and Applications 6 Symmetric Key Encryption standards (DES) 7 Symmetric Key Encryption standards (AES) 8 Diffie-Hellman Key Establishment 9 Public-Key cryptosystems (PKCSv1.5) 10 Digital Signatures 11 Configure a mail agent to support Digital Certificates, send a mail and verify the correctness of this system using the configured parameters. 12 Configure SSH (Secure Shell) and send/receive a file on this connection to verify the correctness of this system using the configured parameters. 13 Configure a firewall to block the following for 5 minutes and verify the correctness of this system

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16. DATA WAREHOUSING AND DATA MINING LAB (A70595)

16.0 SYLLABUS

WEEK 1 1. Introduction to data mining lab 2. Introduction to data mining techniques: association, classification and clustering 3. Data set definition and applying the association rule to manually derive the associations among the data objects in weather data set

WEEK 2 1. Introduction to open source machine learning tool WEKA 2. Open WEKA and Load the data set editor. Get familiarize with the editor operations . WEEK 3 1. Load the weather. Nominal dataset. Use the filter WEKA. Unsupervised, instance. Remove with Values to remove all instances in which the humidity attribute has the value high. To do this, first make the field next to the Choose button show the text Remove with Values. Then click on it to get the Generic Object Editor window, and figure out how to change the filter settings appropriately. 2. Undo the change to the dataset that you just performed, and verify that the data has reverted to its original state

WEEK 4 1. Introduction to different algorithms for generating the clusters by using data set 2. Choosing k-means clustering algorithm for clustering use the Cancer data (.arff) perform clustering with a Euclidean distance function and visually inspect the nature of the clusters.

WEEK 5 1. Exploring the filters available in WEKA and learning about supervised and unsupervised mechanisms 2. Choosing an appropriate filter for classification use the Iris data (.arff) perform classification and visualize the classification tree. WEEK 6 1. The glass dataset glass.arff from the U.S. Forensic Science Service contains data on six types of glass. Glass is described by its refractive index and the chemical elements that it contains; the aim is to classify different types of glass based on these features. This dataset is taken from the UCI datasets, which have been collected by the University of California at Irvine and are freely available on the Web. They are often used as a benchmark for comparing data mining algorithms. Find the dataset glass.arff and load it into the Explorer interface. For your own information, answer the following exercises. How many attributes are there in the dataset? What are their names? What is the class attribute? Run the classification algorithm IBK Use cross-validation to test its performance. MLR Institute of Technology, Dundigal, Hyd-500043 Page 170

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WEEK 7 Data warehousing lab 1. Introduction to Informatica power center 7.1.1and Introduction to Oracle 9i WEEK 8 Adding a Repository a. Create a Source Definition using source connection and import the employee data from source table. b. Organize the columns in the table view to the requirement of Data Analysis.

WEEK 9 1. Create a Target Definition using target connection to the target table. 2. Create tables for transformation and generate SQL to perform transformation.

WEEK 10 Mapping 1. Perform an ETL on Employees database. Select the employee table as the source and the same as the target and assume connectivity and delimiters as pipe without any specific transformations.

WEEK 11 1. Perform an ETL on Employees database. Select the employee table as the source and the same as the target and assume connectivity and delimiters as pipe using expression transformation, filter transformation, router transformation, aggregator transformation and joiner transformation.

2. Perform and ETL on Employees database, connect the source and target and then perform debug on the filter transformation mapping.

WEEK 12 Lookup Using the above mappings perform connected lookup with lookup transformation using natural keys and populate the other keys with default values.

TEXT BOOKS: 1. Jiawei Han, Micheline Kamber, Jian Pei (2012), Data Mining: Concepts and Techniques, 3rd edition, Elsevier, United States of America. REFERENCES: 1. Margaret H Dunham (2006), Data Mining Introductory and Advanced Topics, 2nd edition, Pearson Education, New Delhi, India. 2. Amitesh Sinha (2007), Data Warehousing, Thomson Learning, India. 3. Xingdong Wu, Vipin Kumar (2009), the Top Ten Algorithms in Data Mining, CRC Press, UK.

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16.3 LAB EXPERIMENT SCHEDULE:

Sl.no Week Name of the Exp Date Date No Planned Conducted 1 1 1. Introduction to data mining lab 2. Introduction to data mining techniques: association, classification and clustering 3. Data set definition and applying the association rule to manually derive the associations among the data objects in weather data set

2 2 1. Introduction to open source machine learning tool WEKA 2. Open WEKA and Load the data set editor. Get familiarize with the editor operations

3 3 1. Load the weather. Nominal dataset. Use the filter WEKA. Unsupervised, instance. Remove with Values to remove all instances in which the humidity attribute has the value high. To do this, first make the field next to the Choose button show the text Remove with Values. Then click on it to get the Generic Object Editor window, and figure out how to change the filter settings appropriately. 2. Undo the change to the dataset that you just performed, and verify that the data has reverted to its original state

4 4 1. Introduction to different algorithms for generating the clusters by using data set 2. Choosing k-means clustering algorithm for clustering use the Cancer data (.arff) perform clustering with a Euclidean distance function and visually inspect the nature of the clusters.

5 5 1. Exploring the filters available in WEKA and learning about supervised and unsupervised mechanisms 2. Choosing an appropriate filter for classification use the Iris data (.arff) perform classification and visualize the classification tree

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6 6 The glass dataset glass.arff from the U.S. Forensic Science Service contains data on six types of glass. Glass is described by its refractive index and the chemical elements that it contains; the aim is to classify different types of glass based on these features. This dataset is taken from the UCI datasets, which have been collected by the University of California at Irvine and are freely available on the Web. They are often used as a benchmark for comparing data mining algorithms. Find the dataset glass.arff and load it into the Explorer interface. For your own information, answer the following exercises. How many attributes are there in the dataset? What are their names? What is the class attribute? Run the classification algorithm IBK Use cross-validation to test its performance 7 7 Introduction to Informatica power center 7.1.1and Introduction to Oracle 9i

8 8 Adding a Repository a. Create a Source Definition using source connection and import the employee data from source table. b. Organize the columns in the table view to the requirement of Data Analysis.

9 9 1. Create a Target Definition using target connection to the target table. 2. Create tables for transformation and generate SQL to perform transformation.

10 10 Mapping Perform an ETL on Employees database. Select the employee table as the source and the same as the target and assume connectivity and delimiters as pipe without any specific transformations. 11 11 1. Perform an ETL on Employees database. Select the employee table as the source and the same as the target and assume connectivity and delimiters as pipe using expression transformation, filter transformation, router transformation, aggregator transformation and joiner transformation.

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2. Perform and ETL on Employees database, connect the source and target and then perform debug on the filter transformation mapping 12 12 Lookup Using the above mappings perform connected lookup with lookup transformation. Using natural keys and populate the other keys with default values.

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PROGRAM OUTCOMES (POs): Engineering Graduates will be able to: PO1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems. PO2. Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences. PO3. Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations. PO4. Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions. PO5. Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations. PO6. The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice. PO7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development. PO8. Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice. PO9. Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings. PO10. Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions. PO11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments. PO12. Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change. PROGRAM SPECIFIC OUTCOMES (PSOs): PSO1: Understand the structure, evolutionary changes and development methodologies of software systems to address modern computing challenges. PSO2: Develop intelligent and autonomous systems to cater societal needs especially in the fields of health care, ecommerce, banking, agriculture, cyber security, and insurance.

VISION STATEMENT

VISION OF THE INSTITUTION

Promote academic excellence, research, innovation, and entrepreneurial skills to produce graduates with human values and leadership qualities to serve the nation.

MISSION STATEMENT

MISSION OF THE INSTITUTION Provide student-centric education and training on cutting-edge technologies to make the students globally competitive and socially responsible citizens. Create an environment to strengthen the research, innovation and entrepreneurship to solve societal problems.