Switching-Like Sliding Mode Security Control Against DoS Attacks: A Novel Attack-Related Adaptive Event-Triggered Scheme

Jiancun Wu; Zhiru Cao; Engang Tian; Chen Peng

doi:10.1109/JAS.2025.125189

IEEE/CAA Journal of Automatica Sinica

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Article Navigation > IEEE/CAA Journal of Automatica Sinica > 2025 > In Press, Accepted Manuscript

J. Wu, Z. Cao, E. Tian, and C. Peng, “Switching-like sliding mode security control against DoS attacks: A novel attack-related adaptive event-triggered scheme,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125189

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J. Wu, Z. Cao, E. Tian, and C. Peng, “Switching-like sliding mode security control against DoS attacks: A novel attack-related adaptive event-triggered scheme,” IEEE/CAA J. Autom. Sinica, 2025. doi: 10.1109/JAS.2025.125189

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Switching-Like Sliding Mode Security Control Against DoS Attacks: A Novel Attack-Related Adaptive Event-Triggered Scheme

doi: 10.1109/JAS.2025.125189

Funds: This work was supported in part by the Shanghai Natural Science Foundation (24ZR1454700), in part by the National Natural Science Foundation of China (62173231, 62203288, 62173218), and in part by the Shanghai Pujiang Program (23PJD033)

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Author Bio:
Jiancun Wu received the B.Sc. degree in Mathematics in 2013 from Huainan Normal University, Huainan, China, the M.Sc degree in Operations Research and Cybernetics in 2017 from China Jiliang University, Hangzhou, China, and the Ph.D. degree in Control Theory and Control Engineering in 2022 from Shanghai University, Shanghai, China. He is currently a Postdoctoral Research Fellow in control theory and engineering with University of Shanghai for Science and Technology, Shanghai, China. From 2019 to 2020, he was a visiting Ph.D. student with Swinburne University of Technology, Melbourne, Australia. His current research interests include networked control systems, event-triggered control, and cyber attacks

Zhiru Cao (Member, IEEE) received the B.Sc. degree in Building Electricity & Intelligence from Nanjing Tech University, Nanjing, China, in 2016, and the Ph.D. degree in Control Science and Engineering from East China University of Science and Technology, Shanghai, China, in 2022. She is currently a Lecturer with the School of Mechatronic Engineering and Automation, Shanghai University, Shanghai. From January 2020 to February 2021, she was a visiting Ph.D. student with the Department of Electronic and Computer Engineering, Brunel University London, Uxbridge, U.K. She also was a Research Assistant with The University of Hong Kong, Hong Kong, China, and the University of Macau, Macau, China. Her current research interests include Markov jump systems, unmanned systems, sliding mode control, finite-time control, and sampled-data control. Dr. Cao was the recipient of the Best Doctoral Dissertation Award of Shanghai Association of Automation in 2022, Best Paper Award of Shanghai Association of Automation in 2023, Youth Outstanding Paper Award of Shanghai Association for Artificial Intelligence in 2023, Second Shanghai Natural Science Award in 2023. She is a committee member of IEEE IES, CAA, CICC, SAA; guest editor of the Springer CCIS proceedings

Engang Tian (Senior Member, IEEE) received the B.Sc. degree in mathematics from Shandong Normal University, Jinan, China, in 2002, the M.Sc. degree in operations research and cybernetics from Nanjing Normal University, Nanjing, China, in 2005, and the Ph.D. degree in control theory and control engineering from Donghua University, Shanghai, China, in 2008. From 2011 to 2012, he was a Postdoctoral Research Fellow with the Hong Kong Polytechnic University, Hong Kong. From 2015 to 2016, he was a Visiting Scholar with the Department of Information Systems and Computing, Brunel University London, Uxbridge, U.K. From 2008 to 2018, he was an associate professor and then a professor with the School of Electrical and Automation Engineering, Nanjing Normal University. In 2018, he was appointed as an Eastern Scholar by the Municipal Commission of Education, Shanghai, China, and joined University of Shanghai for Science and Technology, Shanghai, China. He is currently a professor with the School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai. In 2023, he was granted IEEE Outstanding Leadership Award. He has published more than 150 papers in refereed international journals. His research interests include networked control systems, cyber attack, as well as nonlinear stochastic control and filtering

Chen Peng (Senior Member, IEEE) received the M.Sc. and Ph.D. degrees from the Chinese University of Mining Technology, Xuzhou, China, in 1999 and 2002, respectively. From November 2004 to January 2005, he was a Research Associate with the University of Hong Kong, Hong Kong. From July 2006 to August 2007, he was a Visiting Scholar with the Queensland University of Technology, Brisbane, QLD, Australia. From July 2011 to August 2012, he was a Postdoctoral Research Fellow with Central Queensland University, Rockhampton, QLD, Australia. In 2012, he was appointed as an Eastern Scholar with the Municipal Commission of Education, Shanghai, China, and joined Shanghai University, Shanghai. His current research interests include networked control systems, distributed control systems, smart grid, and intelligent control systems. Prof. Peng is an Associate Editor of a number of international journals, including the IEEE Transactions on Industrial Informatics, Information Sciences, and Transactions of the Institute of Measurement and Control. He was named a Highly Cited Researcher in 2020, 2021 and 2022 by Clarivate Analytics
Corresponding author: Jiancun Wu, e-mail: jiancunwu@usst.edu.cn
Received Date: 2024-11-04
Revised Date: 2024-12-27
Accepted Date: 2025-01-10

Available Online: 2025-06-10

Abstract

Abstract

In this paper, a security defense issue is investigated for networked control systems susceptible to stochastic Denial of Service (DoS) attacks by using the sliding mode control method. To utilize network communication resources more effectively, a novel adaptive event-triggered (AET) mechanism is introduced, whose triggering coefficient can be adaptively adjusted according to the evolution trend of system states. Differing from existing ET mechanisms, the proposed one demonstrates exceptional relevance and flexibility. It is closely related to attack probability, and its triggering coefficient dynamically adjusts depending on the presence or absence of an attack. To leverage attacker information more effectively, a switching-like sliding mode security controller is designed, which can autonomously select different controller gains based on the sliding function representing the attack situation. Sufficient conditions for the existence of the switching-like sliding mode secure controller are presented to ensure the stochastic stability of the system and the reachability of the sliding surface. Compared with existing time-invariant control strategies within the triggered interval, more resilient defense performance can be expected since the correlation with attack information is established in both the proposed AET scheme and the control strategy. Finally, a simulation example is conducted to verify the effectiveness and feasibility of the proposed security control method.
- Adaptive event-triggered mechanism,
- denial of service (DoS) attacks,
- networked control systems (NCSs),
- sliding mode control

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References

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Switching-Like Sliding Mode Security Control Against DoS Attacks: A Novel Attack-Related Adaptive Event-Triggered Scheme

doi: 10.1109/JAS.2025.125189

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