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Stealthy false data injection attacks with resource constraints against multi-sensor estimation systems
Haibin Guo1, Jian Sun2, Zhong-Hua Pang3
1State Key Lab of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China.
Abstract:
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.
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