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Resilient Distributed Set-Based Estimation for Cyber-Physical Systems Under False-Data-Injection Attacks
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DOI：10.1109/TIFS.2025.3630874.png)
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Abstract
En 中文
In this paper, resilient distributed set-based estimation is investigated for cyber-physical systems (CPSs) with unknown-but-bounded (UBB) noises which are characterized by constrained polynomial zonotopes (CPZs). Both generalized intersection of CPZs and diffusion strategy are developed to calculate the measurement update and obtain the estimation set. When the system is vulnerable to malicious false-data-injection (FDI) attacks, the encoding-decoding approach is proposed to preserve privacy, which can also be utilized to improve the attack detection rate. After detecting attacks, the corresponding resilient estimation algorithm is provided to alleviate the impact introduced by attacks. Finally, numerical simulations are provided to illustrate the validity of the presented approaches.
Keywords:
Cyber-physical systems
distributed set-based estimation
false-data-injection attacks
Journal
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8
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5.2K
Citations:
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