Finite-time attack detection for nonlinear complex cyber-physical networks under false data injection attacks

This paper investigates the problem of finite-time attack detection for nonlinear complex cyber-physical networks under false data injection (FDI) attacks. Firstly, a Takagi-Sugeno (T-S) fuzzy model is used to approximate nonlinear complex cyber-physical networks in which the measurement channels ar...

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Bibliographic Details
Published in:Journal of the Franklin Institute 2022-12, Vol.359 (18), p.10510-10524
Main Authors: Huang, Xiaojie, Li, Zhiqiang, Ding, Da-Wei
Format: Article
Language:English
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Summary:This paper investigates the problem of finite-time attack detection for nonlinear complex cyber-physical networks under false data injection (FDI) attacks. Firstly, a Takagi-Sugeno (T-S) fuzzy model is used to approximate nonlinear complex cyber-physical networks in which the measurement channels are injected by FDI attacks. Secondly, based on adding a power integrator technique, a finite-time fuzzy observer is designed to achieve the rapid state observation of complex cyber-physical networks within a finite time by adjusting the observer parameters. Then, an attack detection mechanism consisting of the finite-time fuzzy observer and an attack detector is developed to detect FDI attacks, which can trigger an alarm within a finite time when FDI attacks occur. Finally, simulation results are given to show the effectiveness and superiority of the proposed method.
ISSN:0016-0032
1879-2693
DOI:10.1016/j.jfranklin.2022.07.050