Guo Haibin, Sun Jian, Pang Zhong-Hua
State Key Lab of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China.
State Key Lab of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China; Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401120, China.
ISA Trans. 2022 Aug;127:32-40. doi: 10.1016/j.isatra.2022.02.045. Epub 2022 Mar 4.
This paper mainly investigates how to maximally degrade estimation performance of a cyber-physical system under limited resource. A stealthy false data injection (FDI) attack scheme is proposed to only attack partial sensor channels of a multi-sensor estimation system. The attack stealthiness condition and the compromised estimation error covariance are respectively derived, and then the stealthy attack problem is formed as a constrained optimization problem. An explicit solution of the optimal attack strategy is given and proven. Furthermore, the relationship between the compromised estimation error covariance and the attacked sensor is analyzed, and then the sensor selection principle is derived to decide which sensor channel should be attacked. Finally, two numerical simulation examples are provided to confirm the theoretical analysis results.
本文主要研究如何在资源受限的情况下最大程度地降低信息物理系统的估计性能。提出了一种隐蔽虚假数据注入（FDI）攻击方案，仅对多传感器估计系统的部分传感器通道进行攻击。分别推导了攻击隐蔽性条件和受损估计误差协方差，然后将隐蔽攻击问题构建为一个约束优化问题。给出并证明了最优攻击策略的显式解。此外，分析了受损估计误差协方差与被攻击传感器之间的关系，进而推导了传感器选择原则，以确定应攻击哪个传感器通道。最后，提供了两个数值仿真示例来验证理论分析结果。
