False Signal Injection Attack Detection of Cyber Physical Systems by Event-Triggered Distributed Filtering over Sensor Networks

Abstract

This paper is concerned with false signal injection attack detection mechanism using a novel distributed event-triggered filtering for cyber physical systems over sensor networks. By the Internet of Things, the classic physical systems are transformed to the networked cyber physical systems, which are built with a large number of distributed networked sensors. In order to save the precious network resources, a novel distributed event-triggered strategy is proposed. Under this strategy, to generate the localized residual signals, the event-triggered distributed fault detection filters are proposed. By Lyapunov- Krasovskii functional theory, the distributed fault detection filtering problem can be formulated as stability and an $H_{\infty }$ performance of the residual system. Furthermore, a sufficient condition is derived such that the resultant residual system is stable while the transmission of the sampled data is reduced. Based on this condition, the codesign method of the fault detection filters and the transmission strategy is proposed. An illustrative example is given to show the effectiveness of the proposed method.

This work was supported in part by the Nature Science Foundation of Fujian Province under Grant 2016J05156, China.