Sampled‐data control for cyber physical systems via identifying false data injection attacks

Yu, Peng; Wei, Jingliang; Jia, Ruizhe; Wang, Jimin; Guo, Jin

doi:10.1002/acs.3674

Cited by 2 publications

(2 citation statements)

References 41 publications

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“…Thereinto, the most generic attack are the deception attacks, especially false data injection (FDI) attacks. [29][30][31] The attackers maliciously tamper with data for communication channels of CNs while keeping stealthy. Therefore, the FDI attacks are hidden and adverse for CNs.…”

Section: Introductionmentioning

confidence: 99%

State saturated recursive filtering for nonlinear complex networks with energy harvesting sensors and false data injection attacks

Xu,

Bian,

et al. 2024

Adaptive Control & Signal

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SummaryThe state saturated recursive filtering issue is researched in this article for nonlinear complex networks with energy harvesting sensors and false data injection (FDI) attacks. In communication networks, the energy of the sensors is used to transmit data from sensors to remote filters. Due to ample energy being a prerequisite for the transmission of data, the energy harvesting technology is provided. During the process of data transmission, the measurement signals may be attacked by the false data. Thereinto, the Bernoulli random variables are used to depict FDI attacks. The primary goal is to devise a filter that minimizes the upper bound for the filtering error covariance. Subsequently, a discussion is shown for the proposed filtering bounded analysis for the filtering error. Finally, a numerical simulation experiment is carried out to demonstrate the applicability and effectiveness for the proposed novel filtering algorithm.

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Section: Introductionmentioning

confidence: 99%

State saturated recursive filtering for nonlinear complex networks with energy harvesting sensors and false data injection attacks

Xu,

Bian,

et al. 2024

Adaptive Control & Signal

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“…CPS is usually subjected to various of network attacks, including DoS (denial of service) attacks, spoofing attacks, replay attacks and others 10–12 . Among them, DoS attacks are more likely to occur in practice.…”

Section: Introductionmentioning

confidence: 99%

Binary observation‐based identification for finite impulse response systems under denial of service attacks

Wei,

Jia,

Jing

et al. 2024

Adaptive Control & Signal

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SummaryThis article considers the parameter identification problem for the finite impulse response system based on binary observations under denial of service attacks. First, in addition to designing the identification algorithm for the unknown parameter, and its convergence is verified, simultaneously obtaining the asymptotic normality. Then, based on the convergence speed of the identification algorithm and the covariance matrix of the estimation error, the optimal attack strategy problem is transformed into an optimization problem with constraints, then the optimal solution is given. Furthermore, a defense strategy with dual time‐scale input design method is proposed and its effectiveness is demonstrated. Finally, numerical simulations are applied to evidence the correctness of the raised method.

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Sampled‐data control for cyber physical systems via identifying false data injection attacks

Cited by 2 publications

References 41 publications

State saturated recursive filtering for nonlinear complex networks with energy harvesting sensors and false data injection attacks

State saturated recursive filtering for nonlinear complex networks with energy harvesting sensors and false data injection attacks

Binary observation‐based identification for finite impulse response systems under denial of service attacks

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