Optimal Innovation-Based Deception Attacks on Multi-Channel Cyber–Physical Systems

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Publicado en:Electronics vol. 14, no. 8 (2025), p. 1569
Autor principal: Yang, Xinhe
Otros Autores: Zhu, Ren, Zhou Jingquan, Huang, Jing
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MDPI AG
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100 1 |a Yang, Xinhe  |u School of Information Science and Engineering (School of Cyber Science and Technology), Zhejiang Sci-Tech University, Hangzhou 310018, China; 202220702023@mails.zstu.edu.cn (X.Y.); xinjingh@zstu.edu.cn (J.H.) 
245 1 |a Optimal Innovation-Based Deception Attacks on Multi-Channel Cyber–Physical Systems 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a This article addresses the optimal scheduling problem for linear deception attacks in multi-channel cyber–physical systems. The scenario where the attacker can only attack part of the channels due to energy constraints is considered. The effectiveness and stealthiness of attacks are quantified using state estimation error and Kullback–Leibler divergence, respectively. Unlike existing strategies relying on zero-mean Gaussian distributions, we propose a generalized attack model with Gaussian distributions characterized by time-varying means. Based on this model, an optimal stealthy attack strategy is designed to maximize remote estimation error while ensuring stealthiness. By analyzing correlations among variables in the objective function, the solution is decomposed into a semi-definite programming problem and a 0–1 programming problem. This approach yields the modified innovation and an attack scheduling matrix. Finally, numerical simulations validate the theoretical results. 
653 |a Innovations 
653 |a Scheduling 
653 |a Divergence 
653 |a Communication channels 
653 |a Semidefinite programming 
653 |a Cyber-physical systems 
653 |a Normal distribution 
653 |a Sensors 
653 |a Support vector machines 
653 |a State estimation 
653 |a Error analysis 
653 |a Algorithms 
653 |a Deception 
700 1 |a Zhu, Ren  |u School of Information Science and Engineering (School of Cyber Science and Technology), Zhejiang Sci-Tech University, Hangzhou 310018, China; 202220702023@mails.zstu.edu.cn (X.Y.); xinjingh@zstu.edu.cn (J.H.) 
700 1 |a Zhou Jingquan  |u School of Computer Science and Technology (School of Artificial Intelligence), Zhejiang Sci-Tech University, Hangzhou 310018, China; 202230603146@mails.zstu.edu.cn 
700 1 |a Huang, Jing  |u School of Information Science and Engineering (School of Cyber Science and Technology), Zhejiang Sci-Tech University, Hangzhou 310018, China; 202220702023@mails.zstu.edu.cn (X.Y.); xinjingh@zstu.edu.cn (J.H.) 
773 0 |t Electronics  |g vol. 14, no. 8 (2025), p. 1569 
786 0 |d ProQuest  |t Advanced Technologies & Aerospace Database 
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