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Analysis of Stealthy False Data Injection Attacks Against Networked Control Systems: Three Case Studies

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Abstract

This paper mainly investigates the security problem of a networked control system based on a Kalman filter. A false data injection attack scheme is proposed to only tamper the measurement output, and its stealthiness and effects on system performance are analyzed under three cases of system knowledge held by an attacker and a defender. Firstly, it is derived that the proposed attack scheme is stealthy for a residual-based detector when the attacker and the defender hold the same accurate system knowledge. Secondly, it is proven that the proposed attack scheme is still stealthy even if the defender actively modifies the Kalman filter gain so as to make it different from that of the attacker. Thirdly, the stealthiness condition of the proposed attack scheme based on an inaccurate model is given. Furthermore, for each case, the instability conditions of the closed-loop system under attack are derived. Finally, simulation results are provided to test the proposed attack scheme.

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Author information

Authors and Affiliations

  1. Key Laboratory of Fieldbus Technology and Automation of Beijing, North China University of Technology, Beijing, 100144, China

    Zhonghua Pang & Yuan Fu

  2. National Key Laboratory of Autonomous Intelligent Unmanned Systems, School of Automation, Beijing Institute of Technology, Beijing, 100081, China

    Haibin Guo & Jian Sun

  3. Beijing Institute of Technology Chongqing Innovation Center, Chongqing, 401120, China

    Haibin Guo & Jian Sun

Authors
  1. Zhonghua Pang
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  2. Yuan Fu
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  3. Haibin Guo
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  4. Jian Sun
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Corresponding author

Correspondence to Jian Sun.

Ethics declarations

SUN Jian is an editorial board member for Journal of Systems Science and Complexity and was not involved in the editorial review or the decision to publish this article. All authors declare that there are no competing interests.

Additional information

This work was supported in part by the National Natural Science Foundation of China under Grant Nos. 62173002, 61925303, 62088101, U20B2073, and 61720106011, and the Beijing Natural Science Foundation under Grant No. 4222045.

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Pang, Z., Fu, Y., Guo, H. et al. Analysis of Stealthy False Data Injection Attacks Against Networked Control Systems: Three Case Studies. J Syst Sci Complex 36, 1407–1422 (2023). https://doi.org/10.1007/s11424-022-2120-6

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  • DOI: https://doi.org/10.1007/s11424-022-2120-6

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