Stealthy false data injection attacks with resource constraints against multi-sensor estimation systems

Haibin Guo; Jian Sun; Zhong-Hua Pang

doi:10.1016/j.isatra.2022.02.045

Stealthy false data injection attacks with resource constraints against multi-sensor estimation systems

ISA Trans. 2022 Aug:127:32-40. doi: 10.1016/j.isatra.2022.02.045. Epub 2022 Mar 4.

Authors

Haibin Guo¹, Jian Sun², Zhong-Hua Pang³

Affiliations

¹ State Key Lab of Intelligent Control and Decision of Complex Systems, School of Automation, Beijing Institute of Technology, Beijing 100081, China.
² 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.
³ Key Lab of Fieldbus Technology and Automation of Beijing, North China University of Technology, Beijing 100144, China. Electronic address: zhonghua.pang@ia.ac.cn.

PMID: 35292173
DOI: 10.1016/j.isatra.2022.02.045

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.

Keywords: Cyber–physical systems (CPSs); Resource constraint; State estimation; Stealthy FDI attacks.