Proactive and Dynamic Network Defense


Book Description

This book discusses and summarizes current research issues, identifies challenges, and outlines future directions for proactive and dynamic network defense. This book also presents the latest fundamental research results toward understanding proactive and dynamic network defense by top researchers in related areas. It includes research results that offer formal frameworks to define proactive and dynamic network defense, and develop novel models to analyze and evaluate proactive designs and strategies in computer systems, network systems, cyber-physical systems and wireless networks. A wide variety of scientific techniques have been highlighted to study these problems in the fundamental domain. As the convergence of our physical and digital worlds grows fast pace, protecting information systems from being tampered or unauthorized access is becoming one of the most importance issues. The traditional mechanisms of network defense are built upon a static, passive, and reactive nature, which has insufficient to defend against today's attackers that attempt to persistently analyze, probe, circumvent or fool such mechanisms. It has not yet been fully investigated to address the early stage of “cyber kill chain” when adversaries carry out sophisticated reconnaissance to plan attacks against a defense system. Recently, proactive and dynamic network defense has been proposed as an important alternative towards comprehensive network defense. Two representative types of such defense are moving target defense (MTD) and deception-based techniques. These emerging approaches show great promise to proactively disrupt the cyber-attack kill chain and are increasingly gaining interest within both academia and industry. However, these approaches are still in their preliminary design stage. Despite the promising potential, there are research issues yet to be solved regarding the effectiveness, efficiency, costs and usability of such approaches. In addition, it is also necessary to identify future research directions and challenges, which is an essential step towards fully embracing proactive and dynamic network defense. This book will serve as a great introduction for advanced-level computer science and engineering students who would like to start R&D efforts in the field of proactive and dynamic network defense. Researchers and professionals who work in this related field will also find this book useful as a reference.




Moving Target Defense


Book Description

Moving Target Defense: Creating Asymmetric Uncertainty for Cyber Threats was developed by a group of leading researchers. It describes the fundamental challenges facing the research community and identifies new promising solution paths. Moving Target Defense which is motivated by the asymmetric costs borne by cyber defenders takes an advantage afforded to attackers and reverses it to advantage defenders. Moving Target Defense is enabled by technical trends in recent years, including virtualization and workload migration on commodity systems, widespread and redundant network connectivity, instruction set and address space layout randomization, just-in-time compilers, among other techniques. However, many challenging research problems remain to be solved, such as the security of virtualization infrastructures, secure and resilient techniques to move systems within a virtualized environment, automatic diversification techniques, automated ways to dynamically change and manage the configurations of systems and networks, quantification of security improvement, potential degradation and more. Moving Target Defense: Creating Asymmetric Uncertainty for Cyber Threats is designed for advanced -level students and researchers focused on computer science, and as a secondary text book or reference. Professionals working in this field will also find this book valuable.




Science of Cyber Security


Book Description

This book constitutes the proceedings of the Third International Conference on Science of Cyber Security, SciSec 2021, held in Shanghai, China, in August 2021. The 17 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 50 submissions. These papers cover the following subjects: Cyber Security, Detection, Machine Learning and much more.




Modeling and Design of Secure Internet of Things


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.




Decision and Game Theory for Security


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.




Science of Cyber Security


Book Description

This book constitutes the refereed proceedings of the 5th International Conference on Science of Cyber Security, SciSec 2023, held in Melbourne, VIC, Australia, during July 11–14, 2023. The 21 full papers presented together with 6 short papers were carefully reviewed and selected from 60 submissions. The papers are organized in the topical sections named: ​ACDroid: Detecting Collusion Applications on Smart Devices; Almost Injective and Invertible Encodings for Jacobi Quartic Curves; Decompilation Based Deep Binary-Source Function Matching.







Dynamic Networks And Cyber-security


Book Description

As an under-studied area of academic research, the analysis of computer network traffic data is still in its infancy. However, the challenge of detecting and mitigating malicious or unauthorised behaviour through the lens of such data is becoming an increasingly prominent issue.This collection of papers by leading researchers and practitioners synthesises cutting-edge work in the analysis of dynamic networks and statistical aspects of cyber security. The book is structured in such a way as to keep security application at the forefront of discussions. It offers readers easy access into the area of data analysis for complex cyber-security applications, with a particular focus on temporal and network aspects.Chapters can be read as standalone sections and provide rich reviews of the latest research within the field of cyber-security. Academic readers will benefit from state-of-the-art descriptions of new methodologies and their extension to real practical problems while industry professionals will appreciate access to more advanced methodology than ever before.




Game Theory and Machine Learning for Cyber Security


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.




Cyber Security in Intelligent Computing and Communications


Book Description

This book looks at cyber security challenges with topical advancements in computational intelligence and communication technologies. This book includes invited peer-reviewed chapters on the emerging intelligent computing and communication technology research advancements, experimental outcomes, and cyber security practices, threats, and attacks with challenges. The book begins with a state-of-the-art survey and reviews of cyber security trends and issues. It further covers areas such as developments in intelligent computing and communication, smart healthcare, agriculture, transportation, online education, and many more real-life applications using IoT, big data, cloud computing, artificial intelligence, data science, and machine learning. This book is of interest to graduate/postgraduate students, researchers, and academicians. This book will be a valuable resource for practitioners and professionals working in smart city visualization through secure and intelligent application design, development, deployment to foster digital revolution, and reliable integration of advanced computing and communication technologies with global significance.