Cyberattack Strategies Against Cyber-Physical Systems: From a Control Perspective

Cyberattack Strategies Against Cyber-Physical Systems: From a Control Perspective book cover

Cyberattack Strategies Against Cyber-Physical Systems: From a Control Perspective

Author(s): Sheng Gao (Author), Huaicheng Yan (Author), Hao Zhang (Author), Yunkai Lv (Author), Zhichen Li (Author), Meng Wang (Author)

  • Publisher: Springer
  • Publication Date: May 27, 2026
  • Language: English
  • Print length: 243 pages
  • ISBN-10: 9819596440
  • ISBN-13: 9789819596447

Book Description

This book mainly focuses on the key technologies and important issues related to cyberattack strategy design against cyber-physical systems from the perspective of the attacker. Chapter 1 introduces the concept of cyber-physical systems, the significance of their cybersecurity, and research progress both domestically and internationally. Chapters 2–8 present research results on DoS attacks and FDI attacks under model-based, data-driven, time-varying delay, and game-based scenarios. This book demonstrates the effectiveness and superiority of the theoretical methods through simulation and physical examples. This provides defenders with insights into attack behaviors while establishing a theoretical foundation for developing more robust defense mechanisms.

Editorial Reviews

From the Back Cover

This book mainly focuses on the key technologies and important issues related to cyberattack strategy design against cyber-physical systems from the perspective of the attacker. Chapter 1 introduces the concept of cyber-physical systems, the significance of their cybersecurity, and research progress both domestically and internationally. Chapters 2–8 present research results on DoS attacks and FDI attacks under model-based, data-driven, time-varying delay, and game-based scenarios. This book demonstrates the effectiveness and superiority of the theoretical methods through simulation and physical examples. This provides defenders with insights into attack behaviors while establishing a theoretical foundation for developing more robust defense mechanisms.

About the Author

Sheng Gao received the B.Sc. degree in automation from Donghua University, Shanghai, China, in 2019, and the Ph.D. degree in control science and engineering from Tongji University, Shanghai, China, in 2025. He is currently a postdoctoral fellow with the School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China. He was a recipient of the Inaugural Young Elite Scientists Sponsorship Program by CAST, Doctoral Student Special Plan in 2024. His current research interests include optimal control, cyber-physical systems, robot, and cyber security.

Huaicheng Yan received his B.Sc. degree in automatic control from Wuhan University of Technology, China, in 2001, and the Ph.D. degree in control theory and control engineering from Huazhong University of Science and Technology, China, in 2007. Currently, he is a professor with the Faculty of Artificial Intelligence, Shanghai University of Electric Power, Shanghai, China. He was a recipient of the Leading Talent of National Ten Thousand Plan in 2020 and has been a Clarivate Highly Cited Researcher from 2018 to 2025. His research interests include networked control systems, multi-agent systems, and robotics.

Hao Zhang received the B.Sc. degree in automatic control from Wuhan University of Technology, Wuhan, China, in 2001, and received Ph.D. degree in control theory and control engineering from Huazhong University of Science and Technology Wuhan, China, in 2007. Currently, she is a professor with the School of Electronics and Information Engineering, Tongji University, Shanghai, China. Prof. Zhang was a Changjiang scholar distinguished professor under the Ministry of Education in 2023, and also a recipient of the National Science Fund for Excellent Young Scholars of China in 2019. Her research interests include network-based control systems and multi-agent systems.

Yunkai Lv received the B.Sc. degree in measurement and control technology and instrument, and the M.Eng. degree in control science and engineering from Qingdao University of Science and Technology, Qingdao, China, in 2016 and 2019, respectively, and the Ph.D. degree in control science and engineering from Tongji University, Shanghai, China, in 2023. He is currently a professor with the School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China. Prof. Lv was selected into the National Special Support Program for High-Level Talents (Young Top-notch Talents) in 2025. His research interests include network-based control, distributed localization and formation, and multi-agent systems.

Zhichen Li received the B.S. degree in automation and the Ph.D. degree in pattern recognition and intelligent systems from North China Electric Power University, Beijing, China, in 2011 and 2017, respectively. He is currently a professor of East China University of Science and Technology. Prof. Li was a Changjiang young scholar under the Ministry of Education in 2024. His research interests include networked control systems, active disturbance rejection control, robots, and fuzzy modeling and control.

Meng Wang received the B.Eng. degree in Automation from Northeastern University at Qinhuangdao, Qinhuangdao, China, in 2011, and the M.Eng. degree in Control Science and Engineering from Harbin Institute of Technology, Harbin, China, in 2013, and the Ph.D. degree from the Department of Mechanical and Biomedical Engineering, City University of Hong Kong, Hong Kong SAR, China, in 2018. He is currently an associate professor at School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China. His research interests include robust control and filtering, fuzzy systems and control, and their engineering applications.

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