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Sensor attack detection and identification for cyber-physical systems: A data-driven approach

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  • Wang, Kaiyu
  • Ye, Dan

Abstract

This paper investigates the problem of sensor attack detection and identification in cyber-physical systems, leveraging the advantage of zonotopes in dealing with stochastic properties. Unlike previous research that relies on system dynamics knowledge to infer safety boundaries and monitoring schemes, the proposed approach is geared toward addressing the challenges posed by unknown system dynamics, attack strategies, and attack locations. Firstly, we analyze the feasibility of using zonotopes for attack detection and deduce the necessary information quantity and observation window length requirement for effective detection. Subsequently, a zonotopes-based algorithm is proposed for computing the over-approximated reachable set and measurement set from noisy data. Then, an attack detection and identification strategy based on the predicted measurement set is developed. To reduce the computational complexity of the presented detection method, a column truncation algorithm is proposed. The effectiveness of the proposed method is validated through numerical simulations.

Suggested Citation

  • Wang, Kaiyu & Ye, Dan, 2026. "Sensor attack detection and identification for cyber-physical systems: A data-driven approach," Applied Mathematics and Computation, Elsevier, vol. 520(C).
    • Handle: RePEc:eee:apmaco:v:520:y:2026:i:c:s0096300326000068
    DOI: 10.1016/j.amc.2026.129954
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    References listed on IDEAS

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    1. Fan, Xianrui & Tong, Shaocheng, 2024. "Fuzzy adaptive resilient decentralized control of nonlinear interconnected cyber-physical systems under false data injection attacks," Applied Mathematics and Computation, Elsevier, vol. 469(C).
    2. Wang, Ziyun & Wang, Xianzhe & Wang, Yan, 2024. "Orthotope-search-expansion-based extended zonotopic Kalman filter design for a discrete-time linear parameter-varying system with a dual-noise term," Applied Mathematics and Computation, Elsevier, vol. 474(C).
    3. Li, Xin & Lei, Anzhi & Zhu, Liangkuan & Ban, Mingfei, 2024. "Improving Kalman filter for cyber physical systems subject to replay attacks: An attack-detection-based compensation strategy," Applied Mathematics and Computation, Elsevier, vol. 466(C).
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