Sinopsis:
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.
Quanyan Zhu received B. Eng. in Honors Electrical Engineering from McGill University in 2006, M. A. Sc. from the University of Toronto in 2008, and Ph.D. from the University of Illinois at Urbana-Champaign (UIUC) in 2013. After stints at Princeton University, he is currently an associate professor at the Department of Electrical and Computer Engineering, New York University (NYU). He is an affiliated faculty member of the Center for Urban Science and Progress (CUSP) at NYU. He is a recipient of many awards, including NSF CAREER Award, NYU Goddard Junior Faculty Fellowship, NSERC Postdoctoral Fellowship (PDF), NSERC Canada Graduate Scholarship (CGS), and Mavis Future Faculty Fellowships. He spearheaded and chaired INFOCOM Workshop on Communications and Control on Smart Energy Systems (CCSES), Midwest Workshop on Control and Game Theory (WCGT), and ICRA workshop on Security and Privacy of Robotics. His current research interests include game theory, machine learning, cyber deception, network optimization and control, smart cities, Internet of Things, and cyber-physical systems. He has served as the general chair or the TPC chair of the 7th and the 11th Conference on Decision and Game Theory for Security (GameSec) in 2016 and 2020, the 9th International Conference on NETwork Games, COntrol and OPtimisation (NETGCOOP) in 2018, the 5th International Conference on Artificial Intelligence and Security (ICAIS 2019) in 2019, and 2020 IEEE Workshop on Information Forensics and Security (WIFS). He has also spearheaded in 2020 the IEEE Control System Society (CSS) Technical Committee on Security, Privacy, and Resilience. He is a co-author of two recent books published by Springer: Cyber-Security in Critical Infrastructures: A Game-Theoretic Approach (with S. Rass, S. Schauer, and S. König) and A Game- and Decision-Theoretic Approach to Resilient Interdependent Network Analysis and Design (with J. Chen).
Zhiheng Xu received his Ph.D. degree in Electrical Engineering from New York University in 2018. After his Ph.D. graduation, he went to Nanyang Technological University, Singapore, working as Research Fellow for two years. Currently, he works as a senior robotics software engineer at the Department of Intelligent Machines, Dyson Company. His research interests include cyber-physical security, artificial intelligence, reinforcement learning, intelligent decision making, and game theory
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