Fusion and detection for multi-sensor systems under false data injection attacks. (January 2023)

• Record Type: Journal Article
• Authors: Hua, Jinxing; Hao, Fei
• Is Part Of: ISA transactions. Volume 132(2023)
• Page Start: 222
• Page End: 234
• Publication Date: 2023-01
• Subjects: Cyber–physical systems (CPSs) -- Multi-sensor -- Detection -- Partially observable Markov decision process (POMDP) -- Expected SARSA; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2022.06.015
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: This article investigates a security problem in cyber–physical systems under multisensory framework. Data packets from each sensor are transmitted to a remote estimator through wireless channels which could be attacked by a attacker and injected false data. Based on the data of reliable sensors and the relativity between reliable and unreliable sensors, a revised multi-sensor Kalman filter fusion algorithm is proposed. Under the proposed algorithm, an optimal linear false data injection attack strategy which is more general with an arbitrary mean of Gaussian distribution is designed. To further improve the detection performance, an Expected SARSA-based attack detection algorithm is proposed. Finally, simulation results based on an unmanned aerial vehicle are provided to illustrate the feasibility and efficiency of the obtained results. Highlights: The optimal FDI attack strategy in multi-sensor fusion Kalman filter remote estimator. The sum of error covariance matrix in a finite time. The closed form of the suboptimal attack strategy. Expected SARSA-based attack detection algorithm.