自动化学报2025，Vol.51Issue(2)：356-365,10.DOI:10.16383/j.aas.c240527
针对信息物理系统远程状态估计的隐蔽虚假数据注入攻击
Stealthy False Data Injection Attacks on Remote State Estimation of Cyber-physical Systems
摘要
Abstract
The optimal strategy for stealthy false data injection(FDI)attacks in cyber-physical system(CPS)is ex-plored from the attacker's perspective.The Kullback-Leibler(K-L)divergence is selected as the evaluation index of attack stealthiness,and the attack signal is designed to keep the attack stealthy and minimize the performance of CPS remote state estimation.First,the statistical characteristics of the residuals are used to calculate the error cov-ariance of remote state estimation,which transforms the FDI optimal strategy problem into a quadratically con-strained optimization problem.Second,under the constraint of attack stealthiness,the optimal policy is derived us-ing Lagrange multiplier method and semi-positive definite programming.Finally,simulation experiments are con-ducted to verify that the method proposed in this paper has significant advantages in terms of stealthiness com-pared with existing methods.关键词
信息物理系统/虚假数据注入攻击/Kullback-Leibler散度/远程状态估计Key words
Cyber-physical system(CPS)/false data injection(FDI)attacks/Kullback-Leibler(K-L)divergence/remote state estimation引用本文复制引用
金增旺,刘茵,刁靖东,王震,孙长银,刘志强..针对信息物理系统远程状态估计的隐蔽虚假数据注入攻击[J].自动化学报,2025,51(2):356-365,10.基金项目
国家重点研发计划(2022YFB3104005),国家自然科学基金(U21B2008,U23B2039),太仓市基础研究计划(TC2022JC17),宁波市自然科学基金(2021J046)资助Supported by National Key Research and Development Pro-gram of China(2022YFB3104005),National Natural Science Foundation of China(U21B2008,U23B2039),Basic Research Programs of Taicang of China(TC2022JC17),and Ningbo Nat-ural Science Foundation of China(2021J046) （2022YFB3104005）
