Study of Database Reliability and Performance in VCL

Total Page:16

File Type:pdf, Size:1020Kb

Study of Database Reliability and Performance in VCL 1 Study of Database Reliability and Performance in VCL By Yeshwanth Kumaraswamy , North Carolina State University Abstract —This Independent study Report aims OPNET. All that is needed to make use of this to solve certain problems experienced by the facility is a valid ID and an Internet connection. current VCL system, including response slowdowns when multiple users query the system Thousands of student access VCL daily, load on the for statistical information, Section 2 handles this System seems to increase significantly, and hence part of the problem. We also address the the ever increase need for performance problem related to backing up large amounts of enhancement. The future plans to extend the access data at frequent intervals of time, and as to how to VCL to students who are not part of NC State to decrease the backup turn around time of the University rings an alarm, and has raised several database component of the system. performance related issues which are discussed in the following sections. There are some major and The solution to these are discussed in Section 3.This report also highlights the major minor changes as suggested in the rest of the report. differences between MYSQL and PostgreSQL, and tries to arrive at a conclusion as to which We aim to enhance the performance by a one of these is best suited for VCL environment. considerable extent. The current VCL system The solution to this is presented in Section 4 of doesn’t make use of stored procedure and hence the report. increases the system load as the entire result set has to be returned. Hence, increases the memory Finally, the problem of whether to distribute demand and caused certain scripts to terminate database services in a single VCL system is prematurely. Many queries currently in use can be addressed in Section 5 of the report. I have tried modified to perform better by making use of better to address these problems with the help of operators and paraphrasing the query based on the simulations, code and theoretical solutions. The nature of the query. The engine used with each actual code has been replaced by plain textual of the table has also been modified depending on description, and the simulation results are the nature of the tables and based on the nature of included in form of a table. the data stored in them. Significant concurrency can be achieved using specific type of table, and decreases the response time. I. INTRODUCTION T his part of the report aims to describe the A detailed comparison between the two leading functionality of the VCL system. The VCL system open source database system is carried out on the is a complex system which allows the user to basis of several parameters that are relevant to VCL reserve a computer with desired set of applications system and a logical conclusion is derived as to and remotely access the reserved system. This which database system is better for VCL provides great deal of flexibility. VCL allows user environment and if a transformation is desired is it to use popular applications like MATLAB,SAS etc feasible. Additional complexity is introduced as the and provides many simulation environments like 2 database system is maintained by a third party and If the application code is written entirely outside of hence convincing them for such a transformation the database, each of these steps would require a could be difficult. network round trip between the database and the application. The time taken to perform these Since the VCL is going to expand, by being open to network trips can easily dominate overall user other community colleges, the number of users will response time. significantly increase in the near future. Hence it B. The solution would make sense to distribute the database services. This part of the solution is discussed in Stored Procedures, allowing to query to be Section 5 of the report. The objective of this report executed on the server and the results to be sent is to address all these problems and provide back , thus avoiding the entire table from being satisfactory solutions to each of the aforementioned loaded into the memory. Client/Server applications problems. Section 6 of this report also predicts the typically have to balance the load between the client possible outlook of VCL in the future, where the PC and the relatively more powerful server services is made open to different regions (divided machine. Using stored program is one of the ways to reduce the load on the client, which might into quadrants). This schematic diagram differs [14] significantly from the cluster based model. This otherwise get overloaded . model involves lot of complication as presented in Network bandwidth is often a serious section 6, but it can also result in a very robust and constraint on client/server applications, execution of efficient system designed to cater the needs of multiple server-side operations in a single stored number of users. program could reduce network traffic. Also, maintaining correct versions of client software in a Section 7 gives the conclusion and future work in client/server environment was often problematic. this domain. Section 8 gives the list of all references Centralizing at least some of the processing on the both Web and bibliographical. server allowed a greater measure of control over core logic. II. HOW TO AVOID AND MITIGATE DATABASE Stored programs offered clear security advantages, REPONSE SLOWDOWNS WHEN MULTIPLE because in the client/server paradigm, end users CONCURRENT REQUESTS ON STATISTICS ARE SENT typically connected directly to the database to run TO THE SYSTEM . the application. By restricting access to stored A. The Problem programs only, users would not be able to perform ad hoc operations against tables and other database There are restrictions on the size of the script that structures. Hence, stored programs can improve the can be in the memory at a particular point of time security of your database server [6] . (say 32 megs), which results in termination of certain scripts hence resulting in an additional delay. Stored procedures add a extra layer of Abstraction The use of stored procedure obviates this problem, to the existing software application. Which means by ensuring only the result sets are returned. that as long as the interface remains the same the underlying table s can change any number of times , [1] One scenario that takes place in the VCL System without any noticeable change in the application. involves an application that may need to accept By using this layer of abstraction we can prevent a input from the end user, read some data in the potential attacker from knowing the structure of the database, decide what statement to execute next, underlying tables. Hence data become safe from retrieve a result, make a decision, execute some being exposed to the outside world [1] SQL, and so on. Stored programs offer a mechanism to abstract data access routines, hiding your implementation behind 3 a procedural interface and making it easier to evolve SQL, and so on. If the application code is written your data structures over time. entirely outside of the database, each of these steps would require a network round trip between the Stored programs can be used to implement database and the application. The time taken to functionality that is needed and can be called from perform these network trips can easily dominate multiple applications, and from multiple places overall user response time. within a single application. Stored programs will reduce network traffic C. Figure considerably. The evidence is this presented in the figure below. Another security advantage inherent in stored programs is their resistance to SQL The figure below shows abstract functioning of a injection attacks. stored procedure here a user named Bob calls a stored procedure called validate_name. The stored Carefully written stored procedures may allow for procedure accesses the table users to find out if the fine grained security permissions to be applied to a name exists and return only the result hence doesn’t database. Each stored procedure written for mysql eat up the memory. can contain security level as either definer or invoker, the former allows the stored procedure to It also mitigates the memory requirement as all be executed with the permissions set for the the execution takes place on the server side and only invoker, the latter allows the procedure to be the result set is being retuned. Hence no more executed with the permissions of the definer who premature termination of script will take place as wrote the code, so the procedure can access all the the memory limit placed on the size of script will tables and data to which the definer is entitled. not increase. And since the only results are returned Hence, client programs might be restricted from accessing the database via any means except those the network will be kept to minimum. that are provided by the available stored procedures The procedure validate_name() can run directly [14] . within the database engine. In a production system, Stored procedures allow for business logic to be this typically means that the procedures run entirely embedded as an API in the database, which can on a specialized database server, which has direct simplify data management and reduce the need to access to the data being accessed. The benefit here encode the logic elsewhere in client programs. This is that network communication costs can be avoided may result in a lesser likelihood of data becoming completely. This becomes particularly important for corrupted through the use of faulty client programs. complex series of SQL statements.
Recommended publications
  • What Is a Complex Adaptive System?
    PROJECT GUTS What is a Complex Adaptive System? Introduction During the last three decades a leap has been made from the application of computing to help scientists ‘do’ science to the integration of computer science concepts, tools and theorems into the very fabric of science. The modeling of complex adaptive systems (CAS) is an example of such an integration of computer science into the very fabric of science; models of complex systems are used to understand, predict and prevent the most daunting problems we face today; issues such as climate change, loss of biodiversity, energy consumption and virulent disease affect us all. The study of complex adaptive systems, has come to be seen as a scientific frontier, and an increasing ability to interact systematically with highly complex systems that transcend separate disciplines will have a profound affect on future science, engineering and industry as well as in the management of our planet’s resources (Emmott et al., 2006). The name itself, “complex adaptive systems” conjures up images of complicated ideas that might be too difficult for a novice to understand. Instead, the study of CAS does exactly the opposite; it creates a unified method of studying disparate systems that elucidates the processes by which they operate. A complex system is simply a system in which many independent elements or agents interact, leading to emergent outcomes that are often difficult (or impossible) to predict simply by looking at the individual interactions. The “complex” part of CAS refers in fact to the vast interconnectedness of these systems. Using the principles of CAS to study these topics as related disciplines that can be better understood through the application of models, rather than a disparate collection of facts can strengthen learners’ understanding of these topics and prepare them to understand other systems by applying similar methods of analysis (Emmott et al., 2006).
    [Show full text]
  • Dimensions of Ecosystem Complexity: Heterogeneity, Connectivity, and History
    ecological complexity 3 (2006) 1–12 available at www.sciencedirect.com journal homepage: http://www.elsevier.com/locate/ecocom Viewpoint Dimensions of ecosystem complexity: Heterogeneity, connectivity, and history M.L. Cadenasso a,*, S.T.A. Pickett b, J.M. Grove c a Hixon Center for Urban Ecology, School of Forestry and Environmental Studies, Yale University, 205 Prospect Street, New Haven, CT 06511, United States b Institute of Ecosystem Studies, Box AB, Millbrook, NY 12545, United States c USDA Forest Service, Northeastern Research Station, 705 Spear Street, P.O. Box 968, Burlington, VT 05401, United States article info abstract Article history: Biocomplexity was introduced to most ecologists through the National Science Foundation’s Received 2 June 2005 grant program, and the literature intended to introduce that program. The generalities of that Received in revised form literature contrast with the abstract and mathematical sophistication of literature from 30 June 2005 physics, systems theory, and indeed even of pioneering ecologists who have translated the Accepted 2 July 2005 conceptintoecology. Thissituation leaves a middle ground, that isboth accessibletoecologists Published on line 23 January 2006 in general, and cognizant of the fundamentals of complexity, to be more completely explored. To help scope this middle ground, and to promote empirical explorations that may be located Keywords: there, we propose a non-exclusive framework for the conceptual territory. While recognizing Biocomplexity the deep foundations in the studies of complex behavior, we take ecological structure as the Framework entry point for framework development. This framework is based on a definition of biocom- Coupled systems plexity as the degree to which ecological systems comprising biological, social and physical Spatial heterogeneity components incorporate spatially explicit heterogeneity, organizational connectivity, and Legacies historical contingency through time.
    [Show full text]
  • Database-Centric Programming for Wide-Area Sensor Systems
    Database-Centric Programming for Wide-Area Sensor Systems 1 2 1 2 Shimin Chen , Phillip B. Gibbons , and Suman Nath ; 1 Carnegie Mellon University fchensm,[email protected] 2 Intel Research Pittsburgh [email protected] Abstract. A wide-area sensor system is a complex, dynamic, resource-rich col- lection of Internet-connected sensing devices. In this paper, we propose X-Tree Programming, a novel database-centric programming model for wide-area sen- sor systems designed to achieve the seemingly conflicting goals of expressive- ness, ease of programming, and efficient distributed execution. To demonstrate the effectiveness of X-Tree Programming in achieving these goals, we have in- corporated the model into IrisNet, a shared infrastructure for wide-area sensing, and developed several widely different applications, including a distributed in- frastructure monitor running on 473 machines worldwide. 1 Introduction A wide-area sensor system [2, 12, 15, 16] is a complex, dynamic, resource-rich collec- tion of Internet-connected sensing devices. These devices are capable of collecting high bit-rate data from powerful sensors such as cameras, microphones, infrared detectors, RFID readers, and vibration sensors, and performing collaborative computation on the data. A sensor system can be programmed to provide useful sensing services that com- bine traditional data sources with tens to millions of live sensor feeds. An example of such a service is a Person Finder, which uses cameras or smart badges to track people and supports queries for a person's current location. A desirable approach for develop- ing such a service is to program the collection of sensors as a whole, rather than writing software to drive individual devices.
    [Show full text]
  • Existing Cybernetics Foundations - B
    SYSTEMS SCIENCE AND CYBERNETICS – Vol. III - Existing Cybernetics Foundations - B. M. Vladimirski EXISTING CYBERNETICS FOUNDATIONS B. M. Vladimirski Rostov State University, Russia Keywords: Cybernetics, system, control, black box, entropy, information theory, mathematical modeling, feedback, homeostasis, hierarchy. Contents 1. Introduction 2. Organization 2.1 Systems and Complexity 2.2 Organizability 2.3 Black Box 3. Modeling 4. Information 4.1 Notion of Information 4.2 Generalized Communication System 4.3 Information Theory 4.4 Principle of Necessary Variety 5. Control 5.1 Essence of Control 5.2 Structure and Functions of a Control System 5.3 Feedback and Homeostasis 6. Conclusions Glossary Bibliography Biographical Sketch Summary Cybernetics is a science that studies systems of any nature that are capable of perceiving, storing, and processing information, as well as of using it for control and regulation. UNESCO – EOLSS The second title of the Norbert Wiener’s book “Cybernetics” reads “Control and Communication in the Animal and the Machine”. However, it is not recognition of the external similaritySAMPLE between the functions of animalsCHAPTERS and machines that Norbert Wiener is credited with. That had been done well before and can be traced back to La Mettrie and Descartes. Nor is it his contribution that he introduced the notion of feedback; that has been known since the times of the creation of the first irrigation systems in ancient Babylon. His distinctive contribution lies in demonstrating that both animals and machines can be combined into a new, wider class of objects which is characterized by the presence of control systems; furthermore, living organisms, including humans and machines, can be talked about in the same language that is suitable for a description of any teleological (goal-directed) systems.
    [Show full text]
  • Strategies and Rubrics for Teaching Chaos and Complex Systems Theories As Elaborating, Self-Organizing, and Fractionating Evolutionary Systems Lynn S
    Strategies and Rubrics for Teaching Chaos and Complex Systems Theories as Elaborating, Self-Organizing, and Fractionating Evolutionary Systems Lynn S. Fichter1,2, E.J. Pyle1,3, S.J. Whitmeyer1,4 ABSTRACT To say Earth systems are complex, is not the same as saying they are a complex system. A complex system, in the technical sense, is a group of ―agents‖ (individual interacting units, like birds in a flock, sand grains in a ripple, or individual units of friction along a fault zone), existing far from equilibrium, interacting through positive and negative feedbacks, forming interdependent, dynamic, evolutionary networks, that possess universality properties common to all complex systems (bifurcations, sensitive dependence, fractal organization, and avalanche behaviour that follows power- law distributions.) Chaos/complex systems theory behaviors are explicit, with their own assumptions, approaches, cognitive tools, and models that must be taught as deliberately and systematically as the equilibrium principles normally taught to students. We present a learning progression of concept building from chaos theory, through a variety of complex systems, and ending with how such systems result in increases in complexity, diversity, order, and/or interconnectedness with time—that is, evolve. Quantitative and qualitative course-end assessment data indicate that students who have gone through the rubrics are receptive to the ideas, and willing to continue to learn about, apply, and be influenced by them. The reliability/validity is strongly supported by open, written student comments. INTRODUCTION divided into fractions through the addition of sufficient Two interrelated subjects are poised for rapid energy because of differences in the size, weight, valence, development in the Earth sciences.
    [Show full text]
  • What Is a Complex System?
    What is a Complex System? James Ladyman, James Lambert Department of Philosophy, University of Bristol, U.K. Karoline Wiesner Department of Mathematics and Centre for Complexity Sciences, University of Bristol, U.K. (Dated: March 8, 2012) Complex systems research is becoming ever more important in both the natural and social sciences. It is commonly implied that there is such a thing as a complex system, different examples of which are studied across many disciplines. However, there is no concise definition of a complex system, let alone a definition on which all scientists agree. We review various attempts to characterize a complex system, and consider a core set of features that are widely associated with complex systems in the literature and by those in the field. We argue that some of these features are neither necessary nor sufficient for complexity, and that some of them are too vague or confused to be of any analytical use. In order to bring mathematical rigour to the issue we then review some standard measures of complexity from the scientific literature, and offer a taxonomy for them, before arguing that the one that best captures the qualitative notion of the order produced by complex systems is that of the Statistical Complexity. Finally, we offer our own list of necessary conditions as a characterization of complexity. These conditions are qualitative and may not be jointly sufficient for complexity. We close with some suggestions for future work. I. INTRODUCTION The idea of complexity is sometimes said to be part of a new unifying framework for science, and a revolution in our understanding of systems the behaviour of which has proved difficult to predict and control thus far, such as the human brain and the world economy.
    [Show full text]
  • What Isn't Complexity?
    What Isn’t Complexity? Christopher R. Stephens C3 Centro de Ciencias de la Complejidad and Instituto de Ciencias Nucleares, Universidad Nacional Autonoma de Mexico Circuito Exterior, A. Postal 70-543 Abbreviated Spanish translation published in: Encuentros con la Complejidad, eds. J. Flores Valdes and G. Martinez-Mekler, Siglo XXI (2012). 1. Introduction The question “What is Complexity?” has occupied a great deal of time and paper over the last 20 or so years. There are a myriad different perspectives and “definitions” [1, 2, 3] but still no consensus. But what does the question mean? What do we expect from addressing it? Many think of the goal as finding an intentional definition, whereby necessary and sufficient conditions are specified, according to which anything can be uniquely classified as complex or not. On the other hand, an extensional definition takes a more phenomenological approach, characterizing the set of complex systems by trying to name its members. The intentional route faces the difficulty of either being too restrictive or too general. For example, the notion of computational complexity [4] is mathematically quite rigorous but is too restrictive and, given that maximally complex things are random bit strings, certainly does not capture the intuitive notion of what complexity is. On the other hand, defining complex systems as having many degrees of freedom and non-linear interactions is completely vacuous given that, basically, everything is like that, from a salt crystal to a zebra or from a simple atom to the human brain. One cannot argue that these conditions are not necessary, but they are certainly not sufficient.
    [Show full text]
  • Transformations)
    TRANSFORMACJE (TRANSFORMATIONS) Transformacje (Transformations) is an interdisciplinary refereed, reviewed journal, published since 1992. The journal is devoted to i.a.: civilizational and cultural transformations, information (knowledge) societies, global problematique, sustainable development, political philosophy and values, future studies. The journal's quasi-paradigm is TRANSFORMATION - as a present stage and form of development of technology, society, culture, civilization, values, mindsets etc. Impacts and potentialities of change and transition need new methodological tools, new visions and innovation for theoretical and practical capacity-building. The journal aims to promote inter-, multi- and transdisci- plinary approach, future orientation and strategic and global thinking. Transformacje (Transformations) are internationally available – since 2012 we have a licence agrement with the global database: EBSCO Publishing (Ipswich, MA, USA) We are listed by INDEX COPERNICUS since 2013 I TRANSFORMACJE(TRANSFORMATIONS) 3-4 (78-79) 2013 ISSN 1230-0292 Reviewed journal Published twice a year (double issues) in Polish and English (separate papers) Editorial Staff: Prof. Lech W. ZACHER, Center of Impact Assessment Studies and Forecasting, Kozminski University, Warsaw, Poland ([email protected]) – Editor-in-Chief Prof. Dora MARINOVA, Sustainability Policy Institute, Curtin University, Perth, Australia ([email protected]) – Deputy Editor-in-Chief Prof. Tadeusz MICZKA, Institute of Cultural and Interdisciplinary Studies, University of Silesia, Katowice, Poland ([email protected]) – Deputy Editor-in-Chief Dr Małgorzata SKÓRZEWSKA-AMBERG, School of Law, Kozminski University, Warsaw, Poland ([email protected]) – Coordinator Dr Alina BETLEJ, Institute of Sociology, John Paul II Catholic University of Lublin, Poland Dr Mirosław GEISE, Institute of Political Sciences, Kazimierz Wielki University, Bydgoszcz, Poland (also statistical editor) Prof.
    [Show full text]
  • Complex System Classification
    Complex System Classification C. L. Magee1 O. L. de Weck2 Massachusetts Institute of Technology Massachusetts Institute of Technology Room E60-275 Room 33-410 77 Massachusetts Avenue 77 Massachusetts Avenue Cambridge, MA 02139 Cambridge, MA 02139 Fourteenth Annual International Symposium of the International Council On Systems Engineering (INCOSE) 20 June – 24 June 2004 Abstract The use of terms such as “Engineering Systems”, “System of systems” and others have been coming into greater use over the past decade to denote systems of importance but with implied higher complexity than for the term systems alone. This paper searches for a useful taxonomy or classification scheme for complex Systems. There are two aspects to this problem: 1) distinguishing between Engineering Systems (the term we use) and other Systems, and 2) differentiating among Engineering Systems. Engineering Systems are found to be differentiated from other complex systems by being human-designed and having both significant human complexity as well as significant technical complexity. As far as differentiating among various engineering systems, it is suggested that functional type is the most useful attribute for classification differentiation. Information, energy, value and mass acted upon by various processes are the foundation concepts underlying the technical types. Introduction There are three inter-related reasons for attempting a classification study of complex systems. First, academic activity indicates interest in forming a field of study and by analogy with other fields, a classification framework has often been a major step forward, and a significant accelerator of development of the field. Second, the development of a framework for classification of complex systems may help delineate the “intellectual boundaries” of engineering systems.
    [Show full text]
  • Emergent Complex Systems
    Futures 1994 26(6) 568-582 EMERGENT COMPLEX SYSTEMS Silvio Funtowicz and Jerome R. Ravetz Complex systems are becoming the focus of important innovative research and application in many areas, reflecting the progressive displacement of classical physics and the emergence of a new and creative role for mathematics. This article makes a distinction between ordinary and emergent complexity and argues that a full analysis requires dialectical thinking. In so doing the authors aim to provide a philosophical foundation for post-normal science. The exploratory analysis developed here is complementary to those conducted with a more formal, mathematical approach, and begins to articulate what lies on the other side of that somewhat indistinct divide, the conceptual space called emergent complexity. In response to the new leading problems for science, in which the traditional reductionist approach is patently inadequate, complex systems are becoming the focus of important innovative research and application in many areas.’ This development reflects the progressive displacement of classical physics as the exemplar science of our time, and the emergence of a new and creative role for mathematics. Now, formalisms and computations are no longer taken to represent the core of immutable truth and certainty in a world of flux; but they are used with respect for the variability and uncertainty of the world of experience. The distinction has already been made between simple and complex systems;’ we find it useful to further refine ‘complexity’ into ordinary and emergent. These types are characterized by two different patterns of structure and relationships. In ordinary complexity, the most common pattern is a complementarity of competition and cooperation, with a diversity of elements and subsystems.
    [Show full text]
  • Selforganization, Emergence, and Constraint in Complex Natural
    1 Self­Organization, Emergence, and Constraint in Complex Natural Systems Abstract: Contemporary complexity theory has been instrumental in providing novel rigorous definitions for some classic philosophical concepts, including emergence. In an attempt to provide an account of emergence that is consistent with complexity and dynamical systems theory, several authors have turned to the notion of ​constraints​ on state transitions. Drawing on complexity theory directly, this paper builds on those accounts, further developing the constraint­based interpretation of emergence and arguing that such accounts recover many of the features of more traditional accounts. We show that the constraint­based account of emergence also leads naturally into a meaningful definition of self­organization, another concept that has received increasing attention recently. Along the way, we distinguish between ​order​ and ​organization, ​two concepts which are frequently conflated. Finally, we consider possibilities for future research in the philosophy of complex systems, as well as applications of the distinctions made in this paper. Keywords: Complexity Emergence Self­organization Spontaneous order Dynamical systems Corresponding Author: Jonathan Lawhead, PhD University of Southern California Philosophy & Earth Sciences 3651 Trousdale Parkway Zumberge Hall of Science, 223D Los Angeles, CA 90089­0740 [email protected] 775.287.8005 2 0. Introduction There’s a growing body of multidisciplinary research exploring complexity theory and related ideas. This field has not yet really settled yet, and so there’s plenty of terminological confusion out there. Different people use the same terms to mean different things (witness the constellation of definitions of ‘complexity’ itself). A good understanding of how central concepts in complexity theory fit together will help in applying those concepts to real­world social and scientific problems.
    [Show full text]
  • Chapter 9 – Designing the Database
    Systems Analysis and Design in a Changing World, seventh edition 9-1 Chapter 9 – Designing the Database Table of Contents Chapter Overview Learning Objectives Notes on Opening Case and EOC Cases Instructor's Notes (for each section) ◦ Key Terms ◦ Lecture notes ◦ Quick quizzes Classroom Activities Troubleshooting Tips Discussion Questions Chapter Overview Database management systems provide designers, programmers, and end users with sophisticated capabilities to store, retrieve, and manage data. Sharing and managing the vast amounts of data needed by a modern organization would not be possible without a database management system. In Chapter 4, students learned to construct conceptual data models and to develop entity-relationship diagrams (ERDs) for traditional analysis and domain model class diagrams for object-oriented (OO) analysis. To implement an information system, developers must transform a conceptual data model into a more detailed database model and implement that model in a database management system. In the first sections of this chapter students learn about relational database management systems, and how to convert a data model into a relational database schema. The database sections conclude with a discussion of database architectural issues such as single server databases versus distributed databases which are deployed across multiple servers and multiple sites. Many system interfaces are electronic transmissions or paper outputs to external agents. Therefore, system developers need to design and implement integrity controls and security controls to protect the system and its data. This chapter discusses techniques to provide the integrity controls to reduce errors, fraud, and misuse of system components. The last section of the chapter discusses security controls and explains the basic concepts of data protection, digital certificates, and secure transactions.
    [Show full text]