Research On Deception Attack And Its Detection And Performance Optimization Of Cyber Physical System

With the continuous development of science and technology,control systems have become increasingly complex,and cyber-physical systems are rapidly developing and becoming more and more common.This kind of systems monitor themselves through sensor networks,communicate through layered architectures,and most importantly,can control themselves,resulting in complex integration between networks and physical components.In the future,the interconnection of all things in the world will inevitably require a higher degree of openness in the cyber-physical systems,while higher openness will inevitably lead to higher potential security threats.Once the attack on the cyber-physical systems is performed successfully,the consequences will be hard to imagine.Therefore,it is of theoretical and practical significance to study the security of the systems from the perspective of control and detection.In view of the deception attack of cyber-physical systems,this paper has carried out some research.The main contents and innovations are summarized as follows.(1)In order to achieve the detection objective for malicious replay attack,the stochastic coding scheme is proposed in this paper to make the compromised CPS generate covariance differences of certain data.Different from the existing results,this method detects the replay attack without sacrificing any system performances in normal systems.Based on the coding scheme,two types of detectors are further designed to detect the covariance changes in residual and output,respectively.Moreover,the output-based detector has more low-computing solution process than the residual-based one.(2)In view of the situation of the actuator which is under attack,this paper mainly study the designing method of adaptive compensation controller for system executor when the system executor suffers from constant false data injection attack and bounded time-varied false data injection attack.In order to prevent the impact of false data injection attacks on the system,we design an adaptive compensation control strategy.The application of the adaptive compensation control algorithm to the false data injection attack shows that the designed adaptive law has the advantages of fast convergence speed and accurate parameter estimation.The compensation control algorithm can substantially compensate for the effects of false data injection attacks,and we can prove that all signals of the final closed-loop system are bounded and the state of the system can asymptotically converge to zero.Finally,we provide simulation examples to verify the effectiveness of the state feedback adaptive compensation controller proposed in this chapter.(3)In view of the situation of the sensor which is under attack,this paper studies the optimal attack based on residuals in the case of remote state estimation.The attacker can not only intercept the transmitted data packets,but it can also measure the system state and use the measured data or combination information to design the attack strategy.We obtain the optimal attack strategy by solving convex optimization problems,and provide simulation examples to demonstrate the analysis results.