Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks

Wangli He; Zekun Mo; Qing-Long Han; Feng Qian

doi:10.1109/JAS.2020.1003297

Volume 7 Issue 5

Sep. 2020

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2020 > 7(5): 1326-1334

Wangli He, Zekun Mo, Qing-Long Han and Feng Qian, "Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1326-1334, Sept. 2020. doi: 10.1109/JAS.2020.1003297

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Wangli He, Zekun Mo, Qing-Long Han and Feng Qian, "Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks," IEEE/CAA J. Autom. Sinica, vol. 7, no. 5, pp. 1326-1334, Sept. 2020. doi: 10.1109/JAS.2020.1003297

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Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks

doi: 10.1109/JAS.2020.1003297

Funds: This work was supported by the National Natural Science Foundation of China (61988101, 61922030, 61773163), Shanghai Rising-Star Program (18QA1401400), the International (Regional) Cooperation and Exchange Project (61720106008), the Natural Science Foundation of Shanghai (17ZR1406800), the Fundamental Research Funds for the Central Universities, and the 111 Project (B17017)

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Author Bio:
Wangli He (M’11–SM’19) received the Ph.D. degree in applied mathematics from Southeast University, in 2010. She is currently a Professor with the School of Information Science and Engineering, East China University of Science and Technology. Her research interests include coordinated control of multi-agent systems, control and optimization of complex networks, security of cyber-physical systems and distributed perception and decision of multiple vehicles.She was the Chair of Technical Committee on Networked-based Control Systems and Applications of IEEE Industrial Electronics Society (2018–2019) and the Visiting Associate Professor of Tokyo Metropolitan University (2015–2017). She was the recipient of Excellent Doctoral Thesis Award of Jiangsu Province in 2001, Young Elite Scientist of CAST in 2017, Young Rising Star Award of Shanghai Science and Technology Commission in 2018 and National Outstanding Youth Science Foundation in 2019. In 2020, she won the first prize of Shanghai Natural Science Award. She is now an Associate Editor of IEEE Transactions on Neural Networks and Learning Systems and IEEE Access

Zekun Mo received the B.Sc. degree in electrical engineering and automation from the East China University of Science and Technology, in 2018, where he is currently pursuing the M.Sc. degree in control science and engineering. His research interests include secure consensus, impulsive control, and multi-agent systems

Qing-Long Han (M’09–SM’13–F’19) received the B.Sc. degree in mathematics from Shandong Normal University, in 1983, and the M.Sc. and Ph.D. degrees in control engineering from East China University of Science and Technology, in 1992 and 1997, respectively. From September 1997 to December 1998, he was a Post-doctoral Researcher Fellow with the Laboratoire d’Automatique et d’Informatique Industielle (currently, Laboratoire d’Informatique et d’Automatique pour les Systémes), École Supérieure d’Ingénieurs de Poitiers (currently, École Nationale Supérieure d’Ingénieurs de Poitiers), Université de Poitiers, France. From January 1999 to August 2001, he was a Research Assistant Professor with the Department of Mechanical and Industrial Engineering at Southern Illinois University at Edwardsville, USA. From September 2001 to December 2014, he was Laureate Professor, an Associate Dean (Research and Innovation) with the Higher Education Division, and the Founding Director of the Centre for Intelligent and Networked Systems at Central Queensland University, Australia. From December 2014 to May 2016, he was Deputy Dean (Research), with the Griffith Sciences, and a Professor with the Griffith School of Engineering, Griffith University, Australia. In May 2016, he joined Swinburne University of Technology, Australia, where he is currently Pro Vice-Chancellor (Research Quality) and a Distinguished Professor. His research interests include networked control systems, multi-agent systems, time-delay systems, complex dynamical systems, and neural networks.Professor Han is a Highly Cited Researcher according to Clarivate Analytics (formerly Thomson Reuters). He is a Fellow of the Institution of Engineers Australia. He is an Associate Editor of several international journals, including the IEEE Transactions on Cybernetics, the IEEE Transactions on Industrial Electronics, the IEEE Transactions on Industrial Informatics, the IEEE Industrial Electronics Magazine, the IEEE/CAA Journal of Automatica Sinica, the Control Engineering Practice, and the Information Sciences

Feng Qian received the Ph.D. degree in automation from East China Institute of Chemical Technology, in 1995. He is currently a Vice President and Professor with the East China University of Science and Technology, and a member of the Chinese Academy of Engineering. His research interests include modeling, control, optimization, and integration of complex industrial processes, neural networks, and real-time intelligent control with industrial applications
Corresponding author: W. L. He, Z. K. Mo, and F. Qian are with the Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China (e-mail: wanglihe@ecust.edu.cn; 10141184@mail.ecust.edu.cn; fqian@ecust.edu.cn)
Received Date: 2020-03-10
Accepted Date: 2020-06-10

Available Online: 2020-07-06

Abstract

Abstract

Cyber attacks pose severe threats on synchronization of multi-agent systems. Deception attack, as a typical type of cyber attack, can bypass the surveillance of the attack detection mechanism silently, resulting in a heavy loss. Therefore, the problem of mean-square bounded synchronization in multi-agent systems subject to deception attacks is investigated in this paper. The control signals can be replaced with false data from controller-to-actuator channels or the controller. The success of the attack is measured through a stochastic variable. A distributed impulsive controller using a pinning strategy is redesigned, which ensures that mean-square bounded synchronization is achieved in the presence of deception attacks. Some sufficient conditions are derived, in which upper bounds of the synchronization error are given. Finally, two numerical simulations with symmetric and asymmetric network topologies are given to illustrate the theoretical results.
- Deception attacks,
- impulsive control,
- multi-agent systems (MASs),
- synchronization

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References

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A mathematical model of leader-following MASs with distributed impulsive control suffered from replacement deception attacks is built, in which the data integrity is destroyed by the occasional replacement of the control signal with the injected bad data. A stochastic variable following Bernoulli distribution is introduced to describe if the attack is successful.
Sufficient conditions for mean-square bounded synchronization are derived in which the nonzero upper bound of the error is given. The attack intensity and the attack tolerance probability related to the design of the impulsive interval, coupling strength are discussed.
For symmetric networks, how to choose the coupling strength, the impulsive interval and the attack intensity and probability the systems can render are also given.
An asymmetric barrier Lyapunov functions (ABLFs) based neural control is proposed.
All states are guaranteed to stay in the pre-given time-varying ranges within finite time.
The system output is driven to track the desired signal as quickly as possible.

Secure Impulsive Synchronization in Lipschitz-Type Multi-Agent Systems Subject to Deception Attacks

doi: 10.1109/JAS.2020.1003297

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