Low-carbon goals, energy crisis, and increasing electricity demand lead to the integration of advanced electronic and communication devices into the smart grid to enable environmental-friendly, real-time, and economic operation and control. However, the vulnerabilities exposed in the IP-based devices and communication networks make the smart grid prone to cyberattacks. For example, the false data injection attack is one of the critical cyberattacks that threatens the system operations such as state estimation, voltage control, economic dispatch, and etc. Observing that the design of cyberattacks on the smart grid depends on the attacker's knowledge of certain key parameters such as the grid topology and line configurations, an innovative defensive mechanism is to proactively perturb these key parameters to prevent the attacker from knowing this related information for constructing cyberattacks. This proactive perturbation strategy is termed as moving target defense (MTD), which mitigates this risk by dynamically altering the power line reactance, making it harder for adversaries to construct effective cyberattacks. Unlike static countermeasures, MTD enhances smart grid cybersecurity by continuously reshaping the attack surface. Since MTD increases the system uncertainty and complexity of the smart grid, the opportunity for the attacker to successfully launch cyberattacks is reduced.
This book provides a comprehensive analysis of the theoretical foundations of MTD, the optimal deployment of this defense strategy, and the deep impact of MTD on the system’s operation and control. To begin with, a thorough literature review is conducted to summarize the cyber-, physical-, and cyber-physical coordinated MTD approaches. Then, a detailed theoretical analysis is provided to validate the effectiveness and completeness of MTD in terms of detecting and mitigating cyberattacks. Furthermore, the hiddenness of MTD is deeply analyzed from the attacker’s perspective, leading to the development of a coordinated defense framework to enhance the MTD’s hiddenness. Given the complexity resulted from the nonlinear AC state estimation, sensitivity-based approximation methods are proposed to quantify the effectiveness and hiddenness of MTD in AC power systems, forming the basis of an optimization framework to balance the MTD’s effectiveness between hiddenness. Finally, considering the proactive activities caused by MTD, its impact on the system’s operation and control, including the operation cost, load frequency control, and small signal stability, is theoretically and numerically analyzed. This book concludes by discussing future research directions and practical strategies for deploying MTD. The presented MTD design and the corresponding research results covered in this book will provide valuable insights for practical MTD deployment and motivate new ideas for strengthening smart grid cybersecurity.
This book will be valuable for researchers, graduate students, and industry professionals seeking a comprehensive understanding of the latest developments in MTD for smart grid cybersecurity. Designed for readers with a background in Electrical & Computer Engineering, Telecommunications, Computer Science, or related disciplines, it provides the necessary foundation to explore advanced defense strategies. The primary audiences include college students specializing in smart grid, Internet of Things, and cybersecurity, as well as researchers, consultants, and executives involved in smart grid cybersecurity and cyber-physical systems. Additionally, the book will be useful for standardization task forces developing advanced defense strategies. Beyond individual readers, institutions such as power utilities, cybersecurity firms, universities, and research organizations will find it a valuable resource for advancing knowledge and practical applications in smart grid cybersecurity.
Prof. Ruilong Deng received the B.Sc. and Ph.D. degrees both in Control Science and Engineering from Zhejiang University, Hangzhou, Zhejiang, China, in 2009 and 2014, respectively. He was a Research Fellow with Nanyang Technological University, Singapore, from 2014 to 2015; an AITF Postdoctoral Fellow with the University of Alberta, Edmonton, AB, Canada, from 2015 to 2018; and an Assistant Professor with Nanyang Technological University, from 2018 to 2019. Currently, he is a Professor with the College of Control Science and Engineering, Zhejiang University; and a Deputy Director of the State Key Laboratory of Industrial Control Technology. His research interests include the smart grid, cyber security, and control systems. He serves/served as an Associate Editor for IEEE Transactions on Smart Grid, IEEE Power Engineering Letters, IEEE/CAA Journal of Automatica Sinica, and IEEE/KICS Journal of Communications and Networks, and a Guest Editor for IEEE Transactions on Cloud Computing, IEEE Transactions on Emerging Topics in Computing, IEEE Journal of Emerging and Selected Topics in Industrial Electronics, and IET Cyber-Physical Systems: Theory & Applications. He also serves/served as a Symposium Chair for IEEE SmartGridComm, IEEE ICPS, and IEEE GLOBECOM.
Prof. Zhenyong Zhang received his Ph.D. degree from Zhejiang University, Hangzhou, China, in 2020, and bachelor degree from Central South University, Changsha, China, in 2015. He was a visiting scholar in Singapore University of Technology and Design, Singapore, from 2018 to 2019. Currently, he is a Professor with the College of Computer Science and Technology, Guizhou University, Guiyang, China. His research interests include cyber-physical system security, applied cryptography, and machine learning security.
Dr. Mengxiang Liu received the B.S. degree in Automation from Tongji University, Shanghai, in 2017 and the Ph.D. degree in Cyberspace Security from Zhejiang University, Hangzhou, in 2022. He was a Research Associate with the Department of Automatic Control and System Engineering, University of Sheffield, Sheffield, UK, from 2023 to 2024. Currently, he is a MSCA Postdoctoral Fellow with the Department of Electrical and Electronic Engineering, Imperial College London, London, UK. His research interests include smart grid, cyber resilience, and cyber-physical co-simulation.
Prof. Peng Cheng received the B.Sc. and Ph.D. degrees in Control Science and Engineering from Zhejiang University, Hangzhou, China, in 2004 and 2009, respectively. Currently, he is a Professor and Dean of the College of Control Science and Engineering, Zhejiang University. His research interests include networked sensing and control, cyber-physical systems, and control system security. He has been awarded the 2020 Changjiang Scholars Chair Professor. He serves as Associate Editors for the IEEE Transactions on Control of Network Systems. He also serves/served as Guest Editors for IEEE Transactions on Automatic Control and IEEE Transactions on Signal and Information Processing over Networks.
