A journal of IEEE and CAA , publishes
high-quality papers in English on original
theoretical/experimental research
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IEEE/CAA Journal of Automatica Sinica
| Citation: | D. Du, Y. Zhang, B. Xu, and M. Fei, “Optimal secure control of networked control systems under false data injection attacks: A multi-stage attack-defense game approach,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 0, pp. 1–3, Oct. 2024. doi: 10.1109/JAS.2023.124005
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X.-M. Zhang, Q.-L. Han, X. Ge, D. Ding, L. Ding, D. Yue, and C. Peng, “Networked control systems: A survey of trends and techniques,” IEEE-CAA J. Autom. Sinica, vol. 7, no. 1, pp. 1–17, 2020. doi: 10.1109/JAS.2019.1911861
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D. Du, M. Zhu, X. Li, M. Fei, S. Bu, L. Wu, and K. Li, “A review on cybersecurity analysis, attack detection, and attack defense methods in cyber-physical power systems,” J. Mod. Power Syst. Clean Energy, vol. 11, no. 3, pp. 727–743, 2023. doi: 10.35833/MPCE.2021.000604
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D. Ding, Z. Wang, and Q.-L. Han, “Neural-network-based consensus control for multiagent systems with input constraints: The event-triggered case,” IEEE Trans. Cybern., vol. 50, no. 8, pp. 3719–3730, 2020. doi: 10.1109/TCYB.2019.2927471
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B. Shen, Z. Wang, D. Wang, and Q. Li, “State-saturated recursive filter design for stochastic time-varying nonlinear complex networks under deception attacks,” IEEE Trans. Neural Netw. Learn. Syst., vol. 31, no. 10, pp. 3788–3800, 2020. doi: 10.1109/TNNLS.2019.2946290
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Y. Huang and J. Zhao, “Active interdiction defence scheme against false data-injection attacks: A stackelberg game perspective, ” IEEE Trans. Cybern., to be published, 2022, doi: 10.1109/TCYB.2022.3222171.
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J. Lian and X. Huang, “Resilient control of networked switched systems against DoS attack,” IEEE Trans. Ind. Inform., vol. 18, no. 4, pp. 2354–2363, 2022. doi: 10.1109/TII.2021.3097722
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C. Wu, X. Li, W. Pan, J. Liu, and L. Wu, “Zero-sum game-based optimal secure control under actuator attacks,” IEEE Trans. Autom. Control, vol. 66, no. 8, pp. 3773–3780, 2021. doi: 10.1109/TAC.2020.3029342
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B. Pang, T. Bian, and Z.-P. Jiang, “Robust policy iteration for continuous-time linear quadratic regulation,” IEEE Trans. Autom. Control, vol. 67, no. 1, pp. 504–511, 2022. doi: 10.1109/TAC.2021.3085510
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A. Scampicchio, A. Aravkin, and G. Pillonetto, “Stable and robust LQR design via scenario approach,” Automatica, vol. 129, p. 109571, 2021. doi: 10.1016/j.automatica.2021.109571
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Y. Yuan, H. Yuan, L. Guo, H. Yang, and S. Sun, “Resilient control of networked control system under dos attacks: A unified game approach,” IEEE Trans. Ind. Inform., vol. 12, no. 5, pp. 1786–1794, 2016. doi: 10.1109/TII.2016.2542208
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Z. Ni and S. Paul, “A multistage game in smart grid security: A reinforcement learning solution,” IEEE Trans. Neural Netw. Learn. Syst., vol. 30, no. 9, pp. 2684–2695, 2019. doi: 10.1109/TNNLS.2018.2885530
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J. Lai, J. Xiong, and Z. Shu, “Model-free optimal control of discrete-time systems with additive and multiplicative noises,” Automatica, vol. 147, p. 110685, 2023. doi: 10.1016/j.automatica.2022.110685
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| [13] |
D. Du, C. Zhang, X. Li, M. Fei, T. Yang, and H. Zhou, “Secure control of networked control systems using dynamic watermarking,” IEEE Trans. Cybern., vol. 52, no. 12, pp. 13 609–13 622, 2022. doi: 10.1109/TCYB.2021.3110402
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