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Information Security Protocol Based System Identification with Binary-Valued Observations

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Abstract

Traditional control does not pay much attention to information security problems in system identification enough, which are important in practical applications. This paper focuses on the security problem of input information in a class of system identification problems with noise and binary-valued observations, presents a cryptography based security protocol, and improves it in the range of allowed errors. During solving the identification problem, the improved security protocol can ensure that the input information is not leaked, and thus, can deal with passive attacks effectively. Besides, a quantitative relationship among the input information, the public key in encryption and the number of participants in the improved protocol is shown. Finally, the simulation results show that, the identification algorithm can still achieve the estimation accuracy by adding the improved security protocol. However, compared with the original identification algorithm, the time complexity of the algorithm with the improved security protocol increases.

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Author information

Authors and Affiliations

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

    Changbao Xu, Yanlong Zhao & Ji-Feng Zhang

  2. School of Mathematical Sciences, University of Chinese Academy of Sciences, Beijing, 100049, China

    Changbao Xu, Yanlong Zhao & Ji-Feng Zhang

Authors
  1. Changbao Xu
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  2. Yanlong Zhao
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  3. Ji-Feng Zhang
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Corresponding author

Correspondence to Changbao Xu.

Additional information

This research was supported by the National Key Basic Research Program of China (973 Program) under Grant No. 2014CB845301 and the National Natural Science Foundation of China under Grant No. 61227902.

This paper was recommended for publication by Editor SUN Jian.

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Xu, C., Zhao, Y. & Zhang, JF. Information Security Protocol Based System Identification with Binary-Valued Observations. J Syst Sci Complex 31, 946–963 (2018). https://doi.org/10.1007/s11424-017-7075-7

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  • DOI: https://doi.org/10.1007/s11424-017-7075-7

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