Optimal Stealthy Joint Attacks Against Distributed State Estimation in Cyber-Physical Systems

被引:1
|
作者
Su, Guangzhen [1 ]
Liu, Kun [1 ]
Wang, Haojun [1 ]
Zhang, Qirui [2 ]
Xia, Yuanqing [1 ]
机构
[1] Beijing Inst Technol, Sch Automat, Beijing 100081, Peoples R China
[2] China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou, Peoples R China
来源
基金
中国国家自然科学基金;
关键词
Sensors; State estimation; Technological innovation; Symmetric matrices; Detectors; Sensor systems; Filtering algorithms; Consensus error; cyber-physical systems (CPSs); distributed state estimation; Kullback-Leibler divergence (KLD); optimal stealthy joint attacks; SECURITY;
D O I
10.1109/TCNS.2023.3343413
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This article studies the design of optimal stealthy joint attacks against distributed state estimation in cyber-physical systems to steer the state estimates in all the sensors as close as possible to a common target within finite time. To ensure stealthiness, both the Kullback-Leibler divergence (KLD) between innovations and the KLD between consensus errors with and without attacks at each instant should not exceed given thresholds, respectively. In the case that all the thresholds are equal to zero, the optimal attack is given in the form of an analytical expression. In the cases that some thresholds are larger than zero, an optimization problem is solved for each case at each instant, and the corresponding attack sequence obtained is proved to be globally optimal. Finally, a numerical example is adopted to verify the effectiveness of the proposed optimal attack strategies.
引用
收藏
页码:1597 / 1609
页数:13
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