In this paper, from the perspectives of defenders, we consider the detection problems of false data-injection attacks in cyber-physical systems (CPSs) with white noise. The false data-injection attacks usually modify the sensor data to make CPSs unstable and keep stealth for the χ² detector. To guarantee system security, a novel detector, that is, the summation (SUM) detector, is proposed to detect the false data-injection attacks. Different from the χ² detector, the SUM detector not only utilizes the current compromise information but also collects all historical information to reveal the threat. Its evaluation value also satisfies χ² distribution when no attacks compromise the systems, and the false alarm rate can be restricted to less than any given value by choosing the proper threshold value. Furthermore, an improved false data-injection attack with a time-variable increment coefficient is introduced based on the existing approaches. The effects of the SUM detector are also verified for the traditional and the improved false data-injection attacks, respectively. Finally, some simulation results are given to demonstrate the effectiveness and superiority of the SUM detector.

In this paper, the distributed adaptive event-triggered fault-tolerant consensus of general linear multiagent systems (MASs) is considered. First, in order to deal with multiplicative fault, a distributed event-triggered consensus protocol is designed. Using distributed adaptive online updating strategies, the computation of the minimum eigenvalue of Laplacian matrix is avoided. Second, some adaptive parameters are introduced in trigger function to improve the self-regulation ability of event-triggered mechanism. The new trigger threshold is both state-dependent and time-dependent, which is independent of the number of agents. Then sufficient conditions are derived to guarantee the leaderless and leader-following consensus. On the basis of this, the results are extended to the case of actuator saturation. It is proved the Zeno-behavior of considered event-triggered mechanism is avoided. At last, the effectiveness of the proposed methods are demonstrated by three simulation examples.

This article investigates the adaptive event-triggered secure control design problem for a class of stochastic nonlinear high-order multiagent systems (MASs) subject to denial-of-service (DoS) attacks and actuator faults. The considered systems contain not only unknown random interference terms but also general nonlinear functions that are not required to be globally Lipschitz, in contrast to most of the existing results in the area. To solve the problem of wasted communication resources, the control signal with the relative threshold strategy is designed via the event-triggered control technique. As a class of cyber–physical systems, the securities of MASs are vulnerable to actuator faults and DoS attacks. When the system suffers from coupled DoS attacks and actuator failures, its performance will deteriorate rapidly and even the controlled system will collapse. To overcome this difficulty, a novel fault-tolerant and antiattack control method is proposed, which enables the system to achieve the security control objective even in an insecure network and physical environment. The stability analysis of the system is given by combining the adaptive backstepping recursive design process with stochastic Lyapunov stability theory. It is demonstrated that all the signals of the closed-loop systems are semiglobally uniformly ultimately bounded in probability. Finally, a simulation example is given to illustrate the effectiveness and advantages of the presented scheme.

This article studies the secure tracking consensus problem of nonlinear multiagent systems (MASs) against denial-of-service (DoS) attacks. Two types of DoS attacks, i.e., connectivity-maintained attacks and connectivity-broken attacks, are considered. The resulting topologies caused by DoS attacks may destabilize the consensus performance of MASs. Especially under connectivity-broken attacks, the connectivity between agents is destroyed. To deal with these difficulties, a novel defense strategy consisting of distributed observation and decentralized control is proposed. First, a distributed fixed-time observer (DFTO) is prepared for the case of connectivity-maintained attacks, which can quickly and accurately estimate the leader's information for each follower. Besides, the adverse impact of DoS attacks is completely eliminated. Furthermore, to cope with the problem arising from connectivity-broken attacks, by using an online algorithm of updating label information, an improved resilient DFTO (RDFTO) is further developed, which can preserve those followers having directed paths from the leader to quickly and accurately estimate the leader's information, without being affected by DoS attacks. The developed DFTO and RDFTO have successfully eliminated or weakened the adverse effects caused by DoS attacks. Subsequently, based on the proposed DFTO/RDFTO with the power integrator technique, a fixed-time controller is finally constructed, which realizes the desired transient performance of consensus tracking in the finite-time interval. The effectiveness of the proposed defense strategy is verified by stability analysis and simulation examples.