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Author: Jeffrey Pawlick Publisher: Springer Nature ISBN: 3030660656 Category : Mathematics Languages : en Pages : 192
Book Description
This book introduces game theory as a means to conceptualize, model, and analyze cyber deception. Drawing upon a collection of deception research from the past 10 years, the authors develop a taxonomy of six species of defensive cyber deception. Three of these six species are highlighted in the context of emerging problems such as privacy against ubiquitous tracking in the Internet of things (IoT), dynamic honeynets for the observation of advanced persistent threats (APTs), and active defense against physical denial-of-service (PDoS) attacks. Because of its uniquely thorough treatment of cyber deception, this book will serve as a timely contribution and valuable resource in this active field. The opening chapters introduce both cybersecurity in a manner suitable for game theorists and game theory as appropriate for cybersecurity professionals. Chapter Four then guides readers through the specific field of defensive cyber deception. A key feature of the remaining chapters is the development of a signaling game model for the species of leaky deception featured in honeypots and honeyfiles. This model is expanded to study interactions between multiple agents with varying abilities to detect deception. Game Theory for Cyber Deception will appeal to advanced undergraduates, graduate students, and researchers interested in applying game theory to cybersecurity. It will also be of value to researchers and professionals working on cybersecurity who seek an introduction to game theory.
Author: Jeffrey Pawlick Publisher: Springer Nature ISBN: 3030660656 Category : Mathematics Languages : en Pages : 192
Book Description
This book introduces game theory as a means to conceptualize, model, and analyze cyber deception. Drawing upon a collection of deception research from the past 10 years, the authors develop a taxonomy of six species of defensive cyber deception. Three of these six species are highlighted in the context of emerging problems such as privacy against ubiquitous tracking in the Internet of things (IoT), dynamic honeynets for the observation of advanced persistent threats (APTs), and active defense against physical denial-of-service (PDoS) attacks. Because of its uniquely thorough treatment of cyber deception, this book will serve as a timely contribution and valuable resource in this active field. The opening chapters introduce both cybersecurity in a manner suitable for game theorists and game theory as appropriate for cybersecurity professionals. Chapter Four then guides readers through the specific field of defensive cyber deception. A key feature of the remaining chapters is the development of a signaling game model for the species of leaky deception featured in honeypots and honeyfiles. This model is expanded to study interactions between multiple agents with varying abilities to detect deception. Game Theory for Cyber Deception will appeal to advanced undergraduates, graduate students, and researchers interested in applying game theory to cybersecurity. It will also be of value to researchers and professionals working on cybersecurity who seek an introduction to game theory.
Author: Charles A. Kamhoua Publisher: John Wiley & Sons ISBN: 1119723949 Category : Technology & Engineering Languages : en Pages : 546
Book Description
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.
Author: Charles A. Kamhoua Publisher: John Wiley & Sons ISBN: 1119723922 Category : Technology & Engineering Languages : en Pages : 546
Book Description
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.
Author: Sushil Jajodia Publisher: Springer ISBN: 3319326996 Category : Computers Languages : en Pages : 312
Book Description
This edited volume features a wide spectrum of the latest computer science research relating to cyber deception. Specifically, it features work from the areas of artificial intelligence, game theory, programming languages, graph theory, and more. The work presented in this book highlights the complex and multi-facted aspects of cyber deception, identifies the new scientific problems that will emerge in the domain as a result of the complexity, and presents novel approaches to these problems. This book can be used as a text for a graduate-level survey/seminar course on cutting-edge computer science research relating to cyber-security, or as a supplemental text for a regular graduate-level course on cyber-security.
Author: Quanyan Zhu Publisher: Springer Nature ISBN: 3030647935 Category : Computers Languages : en Pages : 518
Book Description
This book constitutes the refereed proceedings of the 11th International Conference on Decision and Game Theory for Security, GameSec 2020,held in College Park, MD, USA, in October 2020. Due to COVID-19 pandemic the conference was held virtually The 21 full papers presented together with 2 short papers were carefully reviewed and selected from 29 submissions. The papers focus on machine learning and security; cyber deception; cyber-physical systems security; security of network systems; theoretic foundations of security games; emerging topics.
Author: Charles A. Kamhoua Publisher: John Wiley & Sons ISBN: 1119593360 Category : Technology & Engineering Languages : en Pages : 704
Book Description
An essential guide to the modeling and design techniques for securing systems that utilize the Internet of Things Modeling and Design of Secure Internet of Things offers a guide to the underlying foundations of modeling secure Internet of Things' (IoT) techniques. The contributors—noted experts on the topic—also include information on practical design issues that are relevant for application in the commercial and military domains. They also present several attack surfaces in IoT and secure solutions that need to be developed to reach their full potential. The book offers material on security analysis to help with in understanding and quantifying the impact of the new attack surfaces introduced by IoT deployments. The authors explore a wide range of themes including: modeling techniques to secure IoT, game theoretic models, cyber deception models, moving target defense models, adversarial machine learning models in military and commercial domains, and empirical validation of IoT platforms. This important book: Presents information on game-theory analysis of cyber deception Includes cutting-edge research finding such as IoT in the battlefield, advanced persistent threats, and intelligent and rapid honeynet generation Contains contributions from an international panel of experts Addresses design issues in developing secure IoT including secure SDN-based network orchestration, networked device identity management, multi-domain battlefield settings, and smart cities Written for researchers and experts in computer science and engineering, Modeling and Design of Secure Internet of Things contains expert contributions to provide the most recent modeling and design techniques for securing systems that utilize Internet of Things.
Author: Kristin E. Heckman Publisher: Springer ISBN: 3319251333 Category : Computers Languages : en Pages : 251
Book Description
This book presents the first reference exposition of the Cyber-Deception Chain: a flexible planning and execution framework for creating tactical, operational, or strategic deceptions. This methodology bridges the gap between the current uncoordinated patchwork of tactical denial and deception (D&D) techniques and their orchestration in service of an organization’s mission. Concepts for cyber- D&D planning operations and management are detailed within the larger organizational, business, and cyber defense context. It examines the necessity of a comprehensive, active cyber denial scheme. The authors explain the organizational implications of integrating D&D with a legacy cyber strategy, and discuss trade-offs, maturity models, and lifecycle management. Chapters present the primary challenges in using deception as part of a security strategy, and guides users through the steps to overcome common obstacles. Both revealing and concealing fact and fiction have a critical role in securing private information. Detailed case studies are included. Cyber Denial, Deception and Counter Deception is designed as a reference for professionals, researchers and government employees working in cybersecurity. Advanced-level students in computer science focused on security will also find this book useful as a reference or secondary text book.
Author: Tiffany Bao Publisher: Springer Nature ISBN: 3031166132 Category : Computers Languages : en Pages : 252
Book Description
This book introduces recent research results for cyber deception, a promising field for proactive cyber defense. The beauty and challenge of cyber deception is that it is an interdisciplinary research field requiring study from techniques and strategies to human aspects. This book covers a wide variety of cyber deception research, including game theory, artificial intelligence, cognitive science, and deception-related technology. Specifically, this book addresses three core elements regarding cyber deception: Understanding human’s cognitive behaviors in decoyed network scenarios Developing effective deceptive strategies based on human’s behaviors Designing deceptive techniques that supports the enforcement of deceptive strategies The research introduced in this book identifies the scientific challenges, highlights the complexity and inspires the future research of cyber deception. Researchers working in cybersecurity and advanced-level computer science students focused on cybersecurity will find this book useful as a reference. This book also targets professionals working in cybersecurity. Chapter 'Using Amnesia to Detect Credential Database Breaches' and Chapter 'Deceiving ML-Based Friend-or-Foe Identification for Executables' are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
Author: Branislav Bošanský Publisher: Springer Nature ISBN: 3030903702 Category : Computers Languages : en Pages : 385
Book Description
This book constitutes the refereed proceedings of the 12th International Conference on Decision and Game Theory for Security, GameSec 2021,held in October 2021. Due to COVID-19 pandemic the conference was held virtually. The 20 full papers presented were carefully reviewed and selected from 37 submissions. The papers focus on Theoretical Foundations in Equilibrium Computation; Machine Learning and Game Theory; Ransomware; Cyber-Physical Systems Security; Innovations in Attacks and Defenses.
Author: Stefan Rass Publisher: Springer Nature ISBN: 3030469085 Category : Computers Languages : en Pages : 297
Book Description
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.
Author: Jeffrey Pawlick
Author: Jeffrey Pawlick
Author: Charles A. Kamhoua
Author: Charles A. Kamhoua
Author: Sushil Jajodia
Author: Quanyan Zhu
Author: Charles A. Kamhoua
Author: Kristin E. Heckman
Author: Tiffany Bao
Author: Branislav Bošanský
Author: Stefan Rass