Theoretical Cybersecurity

This book presents a compendium of selected game- and decision-theoretic models to achieve and assess the security of critical infrastructures. Given contemporary reports on security incidents of various kinds, we can see a paradigm shift to attacks of an increasingly heterogeneous nature, combining different techniques into what we know as an advanced persistent threat. Security precautions must match these diverse threat patterns in an equally diverse manner; in response, this book provides a wealth of techniques for protection and mitigation. Much traditional security research has a narrow focus on specific attack scenarios or applications, and strives to make an attack “practically impossible.” A more recent approach to security views it as a scenario in which the cost of an attack exceeds the potential reward. This does not rule out the possibility of an attack but minimizes its likelihood to the least possible risk. The book follows this economic definition of security, offering a management scientific view that seeks a balance between security investments and their resulting benefits. It focuses on optimization of resources in light of threats such as terrorism and advanced persistent threats. Drawing on the authors’ experience and inspired by real case studies, the book provides a systematic approach to critical infrastructure security and resilience. Presenting a mixture of theoretical work and practical success stories, the book is chiefly intended for students and practitioners seeking an introduction to game- and decision-theoretic techniques for security. The required mathematical concepts are self-contained, rigorously introduced, and illustrated by case studies. The book also provides software tools that help guide readers in the practical use of the scientific models and computational frameworks.

GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.

There is a distinct lack of theoretical innovation in the cybersecurity industry. This is not to say that innovation is lacking, as new technologies, services, and solutions (as well as buzzwords) are emerging every day. This book will be the first cybersecurity text aimed at encouraging abstract and intellectual exploration of cybersecurity from the philosophical and speculative perspective. Technological innovation is certainly necessary, as it furthers the purveying of goods and services for cybersecurity producers in addition to securing the attack surface of cybersecurity consumers where able. The issue is that the industry, sector, and even academia are largely technologically focused. There is not enough work done to further the trade—the craft of cybersecurity. This book frames the cause of this and other issues, and what can be done about them. Potential methods and directions are outlined regarding how the industry can evolve to embrace theoretical cybersecurity innovation as it pertains to the art, as much as to the science. To do this, a taxonomy of the cybersecurity body of work is laid out to identify how the influences of the industry’s past and present constrain future innovation. Then, cost-benefit analysis and right-sizing of cybersecurity roles and responsibilities—as well as defensible experimentation concepts—are presented as the foundation for moving beyond some of those constraining factors that limit theoretical cybersecurity innovation. Lastly, examples and case studies demonstrate future-oriented topics for cybersecurity theorization such as game theory, infinite-minded methodologies, and strategic cybersecurity implementations. What you’ll learn The current state of the cybersecurity sector and how it constrains theoretical innovation How to understand attacker and defender cost benefit The detect, prevent, and accept paradigm How to build your own cybersecurity box Supporting cybersecurity innovation through defensible experimentation How to implement strategic cybersecurity Infinite vs finite game play in cybersecurity Who This Book Is For This book is for both practitioners of cybersecurity and those who are required to, or choose to, employ such services, technology, or capabilities.

Research Methods for Cyber Security teaches scientific methods for generating impactful knowledge, validating theories, and adding critical rigor to the cyber security field. This book shows how to develop a research plan, beginning by starting research with a question, then offers an introduction to the broad range of useful research methods for cyber security research: observational, mathematical, experimental, and applied. Each research method chapter concludes with recommended outlines and suggested templates for submission to peer reviewed venues. This book concludes with information on cross-cutting issues within cyber security research. Cyber security research contends with numerous unique issues, such as an extremely fast environment evolution, adversarial behavior, and the merging of natural and social science phenomena. Research Methods for Cyber Security addresses these concerns and much more by teaching readers not only the process of science in the context of cyber security research, but providing assistance in execution of research as well. Presents research methods from a cyber security science perspective Catalyzes the rigorous research necessary to propel the cyber security field forward Provides a guided method selection for the type of research being conducted, presented in the context of real-world usage

Attaining meaningful cybersecurity presents a broad societal challenge. Its complexity and the range of systems and sectors in which it is needed mean that successful approaches are necessarily multifaceted. Moreover, cybersecurity is a dynamic process involving human attackers who continue to adapt. Despite considerable investments of resources and intellect, cybersecurity continues to poses serious challenges to national security, business performance, and public well-being. Modern developments in computation, storage and connectivity to the Internet have brought into even sharper focus the need for a better understanding of the overall security of the systems we depend on. Foundational Cybersecurity Research focuses on foundational research strategies for organizing people, technologies, and governance. These strategies seek to ensure the sustained support needed to create an agile, effective research community, with collaborative links across disciplines and between research and practice. This report is aimed primarily at the cybersecurity research community, but takes a broad view that efforts to improve foundational cybersecurity research will need to include many disciplines working together to achieve common goals.

Introductory textbook in the important area of network security for undergraduate and graduate students Comprehensively covers fundamental concepts with newer topics such as electronic cash, bit-coin, P2P, SHA-3, E-voting, and Zigbee security Fully updated to reflect new developments in network security Introduces a chapter on Cloud security, a very popular and essential topic Uses everyday examples that most computer users experience to illustrate important principles and mechanisms Features a companion website with Powerpoint slides for lectures and solution manuals to selected exercise problems, available at http://www.cs.uml.edu/~wang/NetSec

Today, when a security incident happens, the top three questions a cyber operation center would ask are: What has happened? Why did it happen? What should I do? Answers to the first two questions form the core of Cyber Situation Awareness (SA). Whether the last question can be satisfactorily addressed is largely dependent upon the cyber situation awareness capability of an enterprise. The goal of this book is to present a summary of recent research advances in the development of highly desirable Cyber Situation Awareness capabilities. The 8 invited full papers presented in this volume are organized around the following topics: computer-aided human centric cyber situation awareness; computer and information science aspects of the recent advances in cyber situation awareness; learning and decision making aspects of the recent advances in cyber situation awareness; cognitive science aspects of the recent advances in cyber situation awareness

GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.