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System identification with binary-valued observations under both denial-of-service attacks and data tampering attacks: defense scheme and its optimality

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Abstract

In this paper, we investigate the defense problem against the joint attacks of denial-of-service attacks and data tampering attacks in the framework of system identification with binary-valued observations. By estimating the key parameters of the joint attack and compensating them in the identification algorithm, a compensation-oriented defense scheme is proposed. Then the identification algorithm of system parameter is designed and is further proved to be consistent. The asymptotic normality of the algorithm is obtained, and on this basis, we propose the optimal defense scheme. Furthermore, the implementation of the optimal defense scheme is discussed. Finally, a simulation example is presented to verify the effectiveness of the main results.

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Acknowledgements

This research was supported by the National Key Research and Development Program of China (2018YFA0703801), the National Natural Science Foundation of China (62173030, 62033010).

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Authors and Affiliations

  1. School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, 100083, China

    Jin Guo, Xuebin Wang & Yanling Zhang

  2. Key Laboratory of Knowledge Automation for Industrial Processes, Ministry of Education, Beijing, 100083, China

    Jin Guo, Xuebin Wang & Yanling Zhang

  3. Key Laboratory of Systems and Control, Institute of Systems Science, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100190, China

    Wenchao Xue & Yanlong Zhao

Authors
  1. Jin Guo
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  2. Xuebin Wang
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  3. Yanling Zhang
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  4. Wenchao Xue
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  5. Yanlong Zhao
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Correspondence to Yanling Zhang.

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Guo, J., Wang, X., Zhang, Y. et al. System identification with binary-valued observations under both denial-of-service attacks and data tampering attacks: defense scheme and its optimality. Control Theory Technol. 20, 114–126 (2022). https://doi.org/10.1007/s11768-021-00074-8

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  • DOI: https://doi.org/10.1007/s11768-021-00074-8

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