H_∞ Fusion-Based FDI Attack Detection For Networked Control Systems

Networked control systems(NCSs)have been widely utilized for many domains owing to a series of advantages such as low wiring cost,easy expansion and maintenance,and high reliability.With the introduction of communication network,it improves the performance and efficiency of existing systems while making NCS vulnerable to False Data Injection(FDI)attacks.Malicious attackers can greatly damage the performance of NCS by intercepting and tampering with the information of actuator and sensor to destroy the integrity of transmitted data.Therefore,it is critical to detect attack signals in time,thus reducing systems'losses.Currently,most of FDI attack detection methods utilize single sensor information to design attack detection strategies,which results in slow alarm response speed and low detection accuracy.Furthermore,due to the distributed H_∞fusion technology can improve detection accuracy and possesses high reliability and strong robustness,this thesis will study the attack signal detection methods based on a distributed H_∞fusion strategy and employ the NCSs under FDI attacks as the research object,emphatically solving problem of alarm response speed.The main works and results are as follows:1)The current research situation at home and abroad is reviewed and analyzed.Based on the introduction of the basic concepts of NCS,the definition of FDI attack is elaborated.Then,the current research situation including main methods of different attack detection methods and multi-sensor fusion estimation at home and abroad are analyzed.Based on this,the subject of this thesis will be constructed into two types of problems,for linear and nonlinear NCSs respectively,studying the multi-sensor information fusion based FDI attack detection problems.2)A distributed H_∞fusion based attack detection method is proposed for linear NCS under executor FDI attacks.Focusing on the problem of slow alarm response speed,a local estimator is designed by using H_∞filtering method to realize the effective estimation of attack signals,which considers the unknown statistical characteristics of attack signals.Particularly,the distributed H_∞fusion estimation strategy is firstly introduced,to design the FDI attack detector.Meanwhile,the problem of network bandwidth limitation is solved by using the logarithmic quantization strategy.Simulation results show that the proposed method can effectively reduce the time of attack detection compared with the existing detection methods based on single sensor information.3)A distributed H_∞fusion based attack detection method is proposed for nonlinear NCS.To solve the similar problem in nonlinear NCS,the H_∞filtering method is also used to design the local estimator.However,considering the existence of nonlinear terms in the system,a new nonlinear fusion detector is constructed by using inequality constraints and the state augmentation method.Simulation results show the feasibility and effectiveness of the proposed method for nonlinear systems.This thesis proposes two distributed H_∞fusion strategy based FDI attack detection methods for linear and nonlinear NCSs respectively,which focus on improving the alarm response speed of FDI attack signal detection.The proposed mehods are superior to the existing methods in terms of response speed and possess great practical significance.