This book introduces a cross-layer design to achieve security and resilience for CPSs (Cyber-Physical Systems). The authors interconnect various technical tools and methods to capture the different properties between cyber and physical layers. Part II of this book bridges the gap between cryptography and control-theoretic tools. It develops a bespoke crypto-control framework to address security and resiliency in control and estimation problems where the outsourcing of computations is possible. Part III of this book bridges the gap between game theory and control theory and develops interdependent impact-aware security defense strategies and cyber-aware resilient control strategies. With the rapid development of smart cities, there is a growing need to integrate the physical systems, ranging from large-scale infrastructures to small embedded systems, with networked communications. The integration of the physical and cyber systems forms Cyber-Physical Systems (CPSs), enabling the use of digital information and control technologies to improve the monitoring, operation, and planning of the systems. Despite these advantages, they are vulnerable to cyber-physical attacks, which aim to damage the physical layer through the cyber network. This book also uses case studies from autonomous systems, communication-based train control systems, cyber manufacturing, and robotic systems to illustrate the proposed methodologies. These case studies aim to motivate readers to adopt a cross-layer system perspective toward security and resilience issues of large and complex systems and develop domain-specific solutions to address CPS challenges. A comprehensive suite of solutions to a broad range of technical challenges in secure and resilient control systems are described in this book (many of the findings in this book are useful to anyone working in cybersecurity). Researchers, professors, and advanced-level students working in computer science and engineering will find this book useful as a reference or secondary text. Industry professionals and military workers interested in cybersecurity will also want to purchase this book.

Smart manufacturing environments are revolutionizing the industrial sector by integrating advanced technologies, such as the Internet of Things (IoT), artificial intelligence (AI), and robotics, to achieve higher levels of efficiency, productivity, and safety. However, the increasing complexity and interconnectedness of these systems also introduce new security challenges that must be addressed to ensure the safety of human workers and the integrity of manufacturing processes. Key topics include risk assessment methodologies, secure communication protocols, and the development of standard specifications to guide the design and implementation of HCPS. Recent research highlights the importance of adopting a multi-layered approach to security, encompassing physical, network, and application layers. Furthermore, the integration of AI and machine learning techniques enables real-time monitoring and analysis of system vulnerabilities, as well as the development of adaptive security measures. Artificial Intelligence Solutions for Cyber-Physical Systems discusses such best practices and frameworks as NIST Cybersecurity Framework, ISO/IEC 27001, and IEC 62443 of advanced technologies. It presents strategies and methods to mitigate risks and enhance security, including cybersecurity frameworks, secure communication protocols, and access control measures. The book also focuses on the design, implementation, and management of secure HCPS in smart manufacturing environments. It covers a wide range of topics, including risk assessment, security architecture, data privacy, and standard specifications, for HCPS. The book highlights the importance of securing communication protocols, the role of artificial intelligence and machine learning in threat detection and mitigation, and the need for robust cybersecurity frameworks in the context of smart manufacturing.

This SpringerBrief introduces methodologies and tools for quantitative understanding and assessment of supply chain risk to critical infrastructure systems. It unites system reliability analysis, optimization theory, detection theory and mechanism design theory to study vendor involvement in overall system security. It also provides decision support for risk mitigation. This SpringerBrief introduces I-SCRAM, a software tool to assess the risk. It enables critical infrastructure operators to make risk-informed decisions relating to the supply chain, while deploying their IT/OT and IoT systems. The authors present examples and case studies on supply chain risk assessment/mitigation of modern connected infrastructure systems such as autonomous vehicles, industrial control systems, autonomous truck platooning and more. It also discusses how vendors of different system components are involved in the overall security posture of the system and how the risk can be mitigated through vendor selection and diversification. The specific topics in this book include: Risk modeling and analysis of IoT supply chains Methodologies for risk mitigation, policy management, accountability, and cyber insurance Tutorial on a software tool for supply chain risk management of IoT These topics are supported by up-to-date summaries of the authors’ recent research findings. The authors introduce a taxonomy of supply chain security and discusses the future challenges and directions in securing the supply chains of IoT systems. It also focuses on the need for joint policy and technical solutions to counter the emerging risks, where technology should inform policy and policy should regulate technology development. This SpringerBrief has self-contained chapters, facilitating the readers to peruse individual topics of interest. It provides a broad understanding of the emerging field of cyber supply chain security in the context of IoT systems to academics, industry professionals and government officials.

This book comprises a set of chapters that introduce various topics pertinent to novel approaches towards enhancing cyber-physical measures for increased security and resilience levels in control systems. The unifying theme of these approaches lies in the utilization of knowledge and models of the physical systems, rather than an attempt to reinvigorate conventional IT-based security measures. The contributing authors present perspectives on network security, game theory, and control, as well as views on how these disciplines can be combined to design resilient, safe, and secure control systems. The book explores how attacks in different forms, such as false data injections and denial-of-service can be very harmful, and may not be detected unless the security measures exploit the physical models. Several applications are discussed, power systems being considered most thoroughly. Because of its interdisciplinary nature—techniques from systems control, game theory, signal processing and computer science all make contributions—Security and Resilience of Control Systems will be of interest to academics, practitioners and graduate students with a broad spectrum of interests.

In an uncertain and complex environment, to ensure secure and stable operations of large-scale power systems is one of the biggest challenges that power engineers have to address today. Traditionally, power system operations and decision-making in controls are based on power system computations of physical models describing the behavior of power systems. Largely, physical models are constructed according to some assumptions and simplifications, and such is the case with power system models. However, the complexity of power system stability problems, along with the system's inherent uncertainties and nonlinearities, can result in models that are impractical or inaccurate. This calls for adaptive or deep-learning algorithms to significantly improve current control schemes that solve decision and control problems. Cyberphysical Infrastructures in Power Systems: Architectures and Vulnerabilities provides an extensive overview of CPS concepts and infrastructures in power systems with a focus on the current state-of-the-art research in this field. Detailed classifications are pursued highlighting existing solutions, problems, and developments in this area. - Gathers the theoretical preliminaries and fundamental issues related to CPS architectures. - Provides coherent results in adopting control and communication methodologies to critically examine problems in various units within smart power systems and microgrid systems. - Presents advanced analysis under cyberphysical attacks and develops resilient control strategies to guarantee safe operation at various power levels.

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.

Medical internet of things (IoT)-based applications are being utilized in several industries and have been shown to provide significant advantages to users in critical health applications. Artificial intelligence (AI) plays a key role in the growth and success of medical IoT applications and IoT devices in the medical sector. To enhance revenue, improve competitive advantage, and increase consumer engagement, the use of AI with medical IoT should be encouraged in the healthcare and medical arena. Revolutionizing Healthcare Through Artificial Intelligence and Internet of Things Applications provides greater knowledge of how AI affects healthcare and medical efficacy in order to improve outputs. It focuses on a thorough and comprehensive introduction to machine learning. Covering topics such as patient treatment, cyber-physical systems, and telemedicine, this premier reference source is a dynamic resource for hospital administrators, medical professionals, government officials, students and faculty of higher education, librarians, researchers, and academicians.

This brief introduces game- and decision-theoretical techniques for the analysis and design of resilient interdependent networks. It unites game and decision theory with network science to lay a system-theoretical foundation for understanding the resiliency of interdependent and heterogeneous network systems. The authors pay particular attention to critical infrastructure systems, such as electric power, water, transportation, and communications. They discuss how infrastructure networks are becoming increasingly interconnected as the integration of Internet of Things devices, and how a single-point failure in one network can propagate to other infrastructures, creating an enormous social and economic impact. The specific topics in the book include: · static and dynamic meta-network resilience game analysis and design; · optimal control of interdependent epidemics spreading over complex networks; and · applications to secure and resilient design of critical infrastructures. These topics are supported by up-to-date summaries of the authors’ recent research findings. The authors then discuss the future challenges and directions in the analysis and design of interdependent networks and explain the role of multi-disciplinary research has in computer science, engineering, public policy, and social sciences fields of study. The brief introduces new application areas in mathematics, economics, and system and control theory, and will be of interest to researchers and practitioners looking for new approaches to assess and mitigate risks in their systems and enhance their network resilience. A Game- and Decision-Theoretic Approach to Resilient Interdependent Network Analysis and Design also has self-contained chapters, which allows for multiple levels of reading by anyone with an interest in game and decision theory and network science.

Master the fundamentals of resilient power grid control applications with this up-to-date resource from four industry leaders Resilient Control Architectures and Power Systems delivers a unique perspective on the singular challenges presented by increasing automation in society. In particular, the book focuses on the difficulties presented by the increased automation of the power grid. The authors provide a simulation of this real-life system, offering an accurate and comprehensive picture of a how a power control system works and, even more importantly, how it can fail. The editors invite various experts in the field to describe how and why power systems fail due to cyber security threats, human error, and complex interdependencies. They also discuss promising new concepts researchers are exploring that promise to make these control systems much more resilient to threats of all kinds. Finally, resilience fundamentals and applications are also investigated to allow the reader to apply measures that ensure adequate operation in complex control systems. Among a variety of other foundational and advanced topics, you'll learn about: The fundamentals of power grid infrastructure, including grid architecture, control system architecture, and communication architecture The disciplinary fundamentals of control theory, human-system interfaces, and cyber security The fundamentals of resilience, including the basis of resilience, its definition, and benchmarks, as well as cross-architecture metrics and considerations The application of resilience concepts, including cyber security challenges, control challenges, and human challenges A discussion of research challenges facing professionals in this field today Perfect for research students and practitioners in fields concerned with increasing power grid automation, Resilient Control Architectures and Power Systems also has a place on the bookshelves of members of the Control Systems Society, the Systems, Man and Cybernetics Society, the Computer Society, the Power and Energy Society, and similar organizations.

This book discusses the latest advances in cyber-physical security and resilience of cyber-physical systems, including cyber-attack detection, isolation, situation awareness, resilient estimation and resilient control under attack. It presents both theoretical results and important applications of the methods. Security and Resilience in Cyber-Physical Systems begins by introducing the topic of cyber-physical security, covering state-of-the-art trends in both theory and applications, as well as some of the emerging methodologies and future directions for research. It then moves on to detail theoretical methods of attack detection, resilient estimation and control within cyber-physical systems, before discussing their various applications, such as power generation and distribution, autonomous systems, wireless communication networks and chemical plants. Focusing on the detection of and accommodation to cyber-attacks on cyber-physical systems, and including both estimation and artificial-intelligence-based methods, this book will be of interest to researchers, engineers and graduate students within the fields of cyber-physical security and resilient control.