Theoretical Cybersecurity

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.

In today’s globalized world, businesses and governments rely heavily on technology for storing and protecting essential information and data. Despite the benefits that computing systems offer, there remains an assortment of issues and challenges in maintaining the integrity and confidentiality of these databases. As professionals become more dependent cyberspace, there is a need for research on modern strategies and concepts for improving the security and safety of these technologies. Modern Theories and Practices for Cyber Ethics and Security Compliance is a collection of innovative research on the concepts, models, issues, challenges, innovations, and mitigation strategies needed to improve cyber protection. While highlighting topics including database governance, cryptography, and intrusion detection, this book provides guidelines for the protection, safety, and security of business data and national infrastructure from cyber-attacks. It is ideally designed for security analysts, law enforcement, researchers, legal practitioners, policymakers, business professionals, governments, strategists, educators, and students seeking current research on combative solutions for cyber threats and attacks.

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.

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.

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

The prevalence of cyber-dependent crimes and illegal activities that can only be performed using a computer, computer networks, or other forms of information communication technology has significantly increased during the last two decades in the USA and worldwide. As a result, cybersecurity scholars and practitioners have developed various tools and policies to reduce individuals' and organizations' risk of experiencing cyber-dependent crimes. However, although cybersecurity research and tools production efforts have increased substantially, very little attention has been devoted to identifying potential comprehensive interventions that consider both human and technical aspects of the local ecology within which these crimes emerge and persist. Moreover, it appears that rigorous scientific assessments of these technologies and policies "in the wild" have been dismissed in the process of encouraging innovation and marketing. Consequently, governmental organizations, public, and private companies allocate a considerable portion of their operations budgets to protecting their computer and internet infrastructures without understanding the effectiveness of various tools and policies in reducing the myriad of risks they face. Unfortunately, this practice may complicate organizational workflows and increase costs for government entities, businesses, and consumers. The success of the evidence-based approach in improving performance in a wide range of professions (for example, medicine, policing, and education) leads us to believe that an evidence-based cybersecurity approach is critical for improving cybersecurity efforts. This book seeks to explain the foundation of the evidence-based cybersecurity approach, review its relevance in the context of existing security tools and policies, and provide concrete examples of how adopting this approach could improve cybersecurity operations and guide policymakers' decision-making process. The evidence-based cybersecurity approach explained aims to support security professionals', policymakers', and individual computer users' decision-making regarding the deployment of security policies and tools by calling for rigorous scientific investigations of the effectiveness of these policies and mechanisms in achieving their goals to protect critical assets. This book illustrates how this approach provides an ideal framework for conceptualizing an interdisciplinary problem like cybersecurity because it stresses moving beyond decision-makers' political, financial, social, and personal experience backgrounds when adopting cybersecurity tools and policies. This approach is also a model in which policy decisions are made based on scientific research findings.

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.