1. Which of the Following Is the Type of Software That Has Self-Replicating
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Security , Hacking, Threats & Tools for Security
SECURITY , HACKING, THREATS & TOOLS FOR SECURITY N.Anupama Asst Professor ANUCET ANU CONTENT Introduction to security Features of security Hacking Security threats Tools to provide security Conclusion SECURITY Security is the protection of assets. The three main aspects are: Prevention Detection re-action Information can be stolen – how to prevent it. Confidential information may be copied and sold - but the theft might not be detected The criminals try to attack and the system should react to stop it. TYPES OF SECURITY Computer Security deals with the prevention and detection of unauthorised actions by users of a computer system. Network security prevent and monitor unauthorized access, misuse, modification, or denial of a computer network and network- accessible resources. Web security deals specifically with security of websites, web applications and web service. Features of security Confidentiality Integrity Availability Non-repudiation Authentication Access Controls Accountability FEATURES OF SECURITY Confidentiality Confidentiality is keeping information secret or private. The prevention of unauthorized disclosure of information. Confidentiality might be important for military, business or personal reasons. Integrity Integrity means that there is consistency in the system - everything is as it is expected to be. Integrity is the authorised writing or modification of information. Data integrity means that the data stored on a computer is the same as the source documents. FEATURES OF SECURITY Availability Information should be accessible and useable upon appropriate demand by an authorized user. Availability is the prevention of unauthorized withholding of information. Non-repudiation Non repudiation is a method of guaranteeing message transmission between parties via digital signature and/or encryption. Non repudiation is often used for digital contracts, signatures and email messages. -
Automatic Classifying of Mac OS X Samples
Automatic Classifying of Mac OS X Samples Spencer Hsieh, Pin Wu and Haoping Liu Trend Micro Inc., Taiwan TREND MICRO LEGAL DISCLAIMER The information provided herein is for general information Contents and educational purposes only. It is not intended and should not be construed to constitute legal advice. The information contained herein may not be applicable to all situations and may not reflect the most current situation. Nothing contained herein should be relied on or acted 4 upon without the benefit of legal advice based on the particular facts and circumstances presented and nothing Introduction herein should be construed otherwise. Trend Micro reserves the right to modify the contents of this document at any time without prior notice. Translations of any material into other languages are intended solely as a convenience. Translation accuracy 6 is not guaranteed nor implied. If any questions arise related to the accuracy of a translation, please refer to Mac OS X Samples Dataset the original language official version of the document. Any discrepancies or differences created in the translation are not binding and have no legal effect for compliance or enforcement purposes. 10 Although Trend Micro uses reasonable efforts to include accurate and up-to-date information herein, Trend Micro makes no warranties or representations of any kind as Classification of Mach-O Files to its accuracy, currency, or completeness. You agree that access to and use of and reliance on this document and the content thereof is at your own risk. Trend Micro disclaims all warranties of any kind, express or implied. 11 Neither Trend Micro nor any party involved in creating, producing, or delivering this document shall be liable for any consequence, loss, or damage, including direct, Malware Families indirect, special, consequential, loss of business profits, or special damages, whatsoever arising out of access to, use of, or inability to use, or in connection with the use of this document, or any errors or omissions in the content 15 thereof. -
Analyzing Android Adware
San Jose State University SJSU ScholarWorks Master's Projects Master's Theses and Graduate Research Spring 2018 Analyzing Android Adware Supraja Suresh San Jose State University Follow this and additional works at: https://scholarworks.sjsu.edu/etd_projects Part of the Computer Sciences Commons Recommended Citation Suresh, Supraja, "Analyzing Android Adware" (2018). Master's Projects. 621. DOI: https://doi.org/10.31979/etd.7xqe-kdft https://scholarworks.sjsu.edu/etd_projects/621 This Master's Project is brought to you for free and open access by the Master's Theses and Graduate Research at SJSU ScholarWorks. It has been accepted for inclusion in Master's Projects by an authorized administrator of SJSU ScholarWorks. For more information, please contact [email protected]. Analyzing Android Adware A Project Presented to The Faculty of the Department of Computer Science San Jose State University In Partial Fulfillment of the Requirements for the Degree Master of Science by Supraja Suresh May 2018 ○c 2018 Supraja Suresh ALL RIGHTS RESERVED The Designated Project Committee Approves the Project Titled Analyzing Android Adware by Supraja Suresh APPROVED FOR THE DEPARTMENTS OF COMPUTER SCIENCE SAN JOSE STATE UNIVERSITY May 2018 Dr. Mark Stamp Department of Computer Science Dr. Katerina Potika Department of Computer Science Fabio Di Troia Department of Mathematics ABSTRACT Analyzing Android Adware by Supraja Suresh Most Android smartphone apps are free; in order to generate revenue, the app developers embed ad libraries so that advertisements are displayed when the app is being used. Billions of dollars are lost annually due to ad fraud. In this research, we propose a machine learning based scheme to detect Android adware based on static and dynamic features. -
Address Munging: the Practice of Disguising, Or Munging, an E-Mail Address to Prevent It Being Automatically Collected and Used
Address Munging: the practice of disguising, or munging, an e-mail address to prevent it being automatically collected and used as a target for people and organizations that send unsolicited bulk e-mail address. Adware: or advertising-supported software is any software package which automatically plays, displays, or downloads advertising material to a computer after the software is installed on it or while the application is being used. Some types of adware are also spyware and can be classified as privacy-invasive software. Adware is software designed to force pre-chosen ads to display on your system. Some adware is designed to be malicious and will pop up ads with such speed and frequency that they seem to be taking over everything, slowing down your system and tying up all of your system resources. When adware is coupled with spyware, it can be a frustrating ride, to say the least. Backdoor: in a computer system (or cryptosystem or algorithm) is a method of bypassing normal authentication, securing remote access to a computer, obtaining access to plaintext, and so on, while attempting to remain undetected. The backdoor may take the form of an installed program (e.g., Back Orifice), or could be a modification to an existing program or hardware device. A back door is a point of entry that circumvents normal security and can be used by a cracker to access a network or computer system. Usually back doors are created by system developers as shortcuts to speed access through security during the development stage and then are overlooked and never properly removed during final implementation. -
A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics
UNIVERSIDAD POLITECNICA´ DE MADRID ESCUELA TECNICA´ SUPERIOR DE INGENIEROS INFORMATICOS´ A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics PH.D THESIS Platon Pantelis Kotzias Copyright c 2019 by Platon Pantelis Kotzias iv DEPARTAMENTAMENTO DE LENGUAJES Y SISTEMAS INFORMATICOS´ E INGENIERIA DE SOFTWARE ESCUELA TECNICA´ SUPERIOR DE INGENIEROS INFORMATICOS´ A Systematic Empirical Analysis of Unwanted Software Abuse, Prevalence, Distribution, and Economics SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF: Doctor of Philosophy in Software, Systems and Computing Author: Platon Pantelis Kotzias Advisor: Dr. Juan Caballero April 2019 Chair/Presidente: Marc Dasier, Professor and Department Head, EURECOM, France Secretary/Secretario: Dario Fiore, Assistant Research Professor, IMDEA Software Institute, Spain Member/Vocal: Narseo Vallina-Rodriguez, Assistant Research Professor, IMDEA Networks Institute, Spain Member/Vocal: Juan Tapiador, Associate Professor, Universidad Carlos III, Spain Member/Vocal: Igor Santos, Associate Research Professor, Universidad de Deusto, Spain Abstract of the Dissertation Potentially unwanted programs (PUP) are a category of undesirable software that, while not outright malicious, can pose significant risks to users’ security and privacy. There exist indications that PUP prominence has quickly increased over the last years, but the prevalence of PUP on both consumer and enterprise hosts remains unknown. Moreover, many important aspects of PUP such as distribution vectors, code signing abuse, and economics also remain unknown. In this thesis, we empirically and sys- tematically analyze in both breadth and depth PUP abuse, prevalence, distribution, and economics. We make the following four contributions. First, we perform a systematic study on the abuse of Windows Authenticode code signing by PUP and malware. -
Malware Xiaowei Yang Previous Lecture
590.05 Lecture 5: Malware Xiaowei Yang Previous lecture • Accountability • OS security Today • Malware Malware: Malicious Software 10/21/13 Malware 4 Viruses, Worms, Trojans, Rootkits • Malware can be classified into several categories, depending on propagaon and concealment • Propagaon 10/21/13 • Virus: human-assisted propagaon (e.g., open email aachment) • Worm: automac propagaon without human assistance Malware • Concealment • Rootkit: modifies operang system to hide its existence • Trojan: provides desirable funcBonality but hides malicious operaon • Various types of payloads, ranging from annoyance to crime 5 Insider Attacks • An insider a)ack is a security breach that is caused or facilitated by someone who is a part of the very organizaon that controls or builds the asset that should be protected. • In the case of malware, an insider aack refers to a security 10/21/13 hole that is created in a soXware system by one of its programmers. Malware 6 Backdoors • A backdoor, which is also someBmes called a trapdoor, is a hidden feature or command in a program that allows a user to perform acBons he or she would not normally be allowed to do. • When used in a normal way, this program performs completely as 10/21/13 expected and adverBsed. • But if the hidden feature is acBvated, the program does something Malware unexpected, oXen in violaon of security policies, such as performing a privilege escalaon. • Benign example: Easter Eggs in DVDs and soXware An Easter egg is an intenBonal inside joke, hidden message, or feature in a work such as a computer program, movie, book, or 7 crossword. -
Common Threats to Cyber Security Part 1 of 2
Common Threats to Cyber Security Part 1 of 2 Table of Contents Malware .......................................................................................................................................... 2 Viruses ............................................................................................................................................. 3 Worms ............................................................................................................................................. 4 Downloaders ................................................................................................................................... 6 Attack Scripts .................................................................................................................................. 8 Botnet ........................................................................................................................................... 10 IRCBotnet Example ....................................................................................................................... 12 Trojans (Backdoor) ........................................................................................................................ 14 Denial of Service ........................................................................................................................... 18 Rootkits ......................................................................................................................................... 20 Notices ......................................................................................................................................... -
Information Security Software Flaws
CS 166: Information Security Software Flaws Prof. Tom Austin San José State University If automobiles had followed the same development cycle as the computer, a Rolls- Royce would today cost $100, get a million miles per gallon, and explode once a year, killing everyone inside. ¾ Robert X. Cringely My software never has bugs. It just develops random features. ¾ Anonymous Why Software? • Why is software as important to security as crypto, access control, protocols? • Virtually all of information security is implemented in software • If your software is subject to attack, your security can be broken – Regardless of strength of crypto, access control or protocols • Software is a poor foundation for security Bad Software is Ubiquitous • NASA Mars Lander (cost $165 million) – Crashed into Mars due to… – …error in converting English and metric units • Denver airport – Baggage handling system --- very buggy software – Delayed airport opening by 11 months – Cost of delay exceeded $1 million/day • MV-22 Osprey – Advanced military aircraft – Faulty software can be fatal Software Issues Alice and Bob Trudy • Find bugs and flaws by • Actively looks for bugs accident and flaws • Hate bad software… • Likes bad software… • …but must learn to live • …and tries to make it with it misbehave • Must make bad • Attacks systems via bad software work software Complexity “Complexity is the enemy of security”, Paul Kocher, Cryptography Research, Inc. System Lines of Code (LOC) Netscape 17 million Space Shuttle 10 million Linux kernel 2.6.0 5 million Windows XP -
Rethinking Security
RETHINKING SECURITY Fighting Known, Unknown and Advanced Threats kaspersky.com/business “Merchants, he said, are either not running REAL DANGERS antivirus on the servers managing point- of-sale devices or they’re not being updated AND THE REPORTED regularly. The end result in Home Depot’s DEMISE OF ANTIVIRUS case could be the largest retail data breach in U.S. history, dwarfing even Target.” 1 Regardless of its size or industry, your business is in real danger of becoming a victim of ~ Pat Belcher of Invincea cybercrime. This fact is indisputable. Open a newspaper, log onto the Internet, watch TV news or listen to President Obama’s recent State of the Union address and you’ll hear about another widespread breach. You are not paranoid when you think that your financial data, corporate intelligence and reputation are at risk. They are and it’s getting worse. Somewhat more controversial, though, are opinions about the best methods to defend against these perils. The same news sources that deliver frightening stories about costly data breaches question whether or not anti-malware or antivirus (AV) is dead, as reported in these articles from PC World, The Wall Street Journal and Fortune magazine. Reports about the death by irrelevancy of anti-malware technology miss the point. Smart cybersecurity today must include advanced anti-malware at its core. It takes multiple layers of cutting edge technology to form the most effective line of cyberdefense. This eBook explores the features that make AV a critical component of an effective cybersecurity strategy to fight all hazards targeting businesses today — including known, unknown and advanced cyberthreats. -
Towards Semi-Automated Detection of Trigger-Based Behavior for Software Security Assurance
Towards Semi-automated Detection of Trigger-based Behavior for Software Security Assurance Dorottya Papp Levente Buttyán Zhendong Ma CrySyS Lab, Dept. of Networked CrySyS Lab, Dept. of Networked Center of Digital Safety and Security, Systems and Services, BME Systems and Services, BME Austrian Institute of Technology Magyar tudósok krt 2. Magyar tudósok krt 2. Donau-City-Straβe 1. Budapest 1117, Hungary Budapest 1117, Hungary Vienna, Austria Center of Digital Safety and Security, [email protected] [email protected] Austrian Institute of Technology Donau-City-Straβe 1. Vienna, Austria [email protected] ABSTRACT 1 INTRODUCTION A program exhibits trigger-based behavior if it performs undocu- Trigger-based behavior in software refers to execution of code that mented, often malicious, functions when the environmental condi- is activated on specific input values (the so called trigger inputs) tions and/or specific input values match some pre-specified criteria. and that performs some undocumented functions. Often, the users Checking whether such hidden functions exist in the program is are not aware of the existence of those undocumented functions important for increasing trustworthiness of software. In this paper, in the software. It is clear that using an application that has such we propose a framework to effectively detect trigger-based behav- hidden functions, which can be triggered by non-legitimate par- ior at the source code level. Our approach is semi-automated: We ties, is dangerous, as those functions can potentially implement use automated source code instrumentation and mixed concrete malicious actions. Indeed, the best examples for trigger-based be- and symbolic execution to generate potentially suspicious test cases havior include backdoors and logic bombs hidden in applications that may trigger hidden, potentially malicious functions. -
A Poisoned Apple: the Analysis of Macos Malware Shlayer By: Minh D
A Poisoned Apple: The Analysis of macOS Malware Shlayer by: Minh D. Nguyen Abstract Historically, the Microsoft Windows operating system family, which currently runs on more than 70 percent of computers in the world,7 has been the main target for malware. However, with the growing popularity of Apple’s MacBook products, the macOS operating system has become a new platform for attackers to target the general computer users. According to the 2016/2017 Security Report of AV-TEST, the number of malware samples for macOS detected in 2016 has increased by an astonishing 370 percent compared to the same figure in 2015.3 In order to address the rising interest of attackers in the macOS operating system, this project provides an analysis of a newly discovered malware for macOS, Shlayer, to reveal a well- known tactic that attackers can utilize to infect machines running on any operating system, and discusses possible countermeasures for this strategy. I. Introduction macOS is often hailed as a more secure operating system compared to its counterpart Microsoft Windows.2 However, in reality, many attacking techniques targeting Windows machines can also be applied to macOS machines. The analysis of the new Shlayer malware, discovered by researchers of Intego in February 2018,1 will reveal a familiar strategy that attackers often utilize to target victim machines without regards of the operating system. With the worldwide growth of macOS usage, it is important to recognize this attacking method and understand that in many cases, the success of an attack does not depend on the security of the operating system but on the awareness of the user. -
Adobe Acrobat Pro Reset Document Password
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