子空间拓扑
鉴定(生物学)
计算机科学
投影(关系代数)
块(置换群论)
过程(计算)
探测器
信息物理系统
数据挖掘
算法
人工智能
数学
电信
生物
操作系统
植物
几何学
作者
Zhengen Zhao,Yunsong Xu,Yuzhe Li,Ziyang Zhen,Ying Yang,Yang Shi
出处
期刊:IEEE Transactions on Automatic Control
[Institute of Electrical and Electronics Engineers]
日期:2023-10-01
卷期号:68 (10): 6330-6337
被引量:5
标识
DOI:10.1109/tac.2022.3230360
摘要
This article studies the issues of data-driven attack detection and identification for cyber-physical systems under sparse sensor attacks. First, based on the available input and output datasets, a data-driven monitor is formulated with the following two objectives: attack detection and attack identification. Then, with the subspace approach, a data-driven attack detection policy is presented, wherein the attack detector is designed directly by the process data. A subspace projection-based attack identification scheme is proposed via designing a bank of projection filters to determine the locations of attacked sensors. Moreover, the sparse recovery technique is adopted to decrease the combinatorial complexity of the subspace projection-based identification method. The attack identification is recast into a block-sparse recovery problem. Finally, the proposed methods are verified by the simulations on a flight vehicle system.
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