Adaptive fault estimation for cyber-physical systems with intermittent DoS attacks

Almost Sure Stability of Complex-Valued Complex Networks: A Noise-Based Delayed Coupling Under Random Denial-of-Service Attacks

This article is concerned with stability for stochastic complex-valued delayed complex networks under random denial-of-service (RDoS) attacks. Different from the existing literature on the stability of stochastic complex-valued systems that concentrate on moment stability, we investigate almost sure stability (ASS), where noise plays a stabilizing role. It is noted that, besides the vertex systems influenced by noise, the interactions among vertices are also at the mercy of noise. As a consequence, an innovative noise-based delayed coupling (NDC) in the presence of RDoS attacks is proposed first to accomplish the stability of complex-valued networks, where the RDoS attacks have a certain probability of triumphantly interfering with communications at active intervals of attackers. Namely, RDoS attacks considered are randomly launched at active periods, which is more realistic. In terms of the Lyapunov method and stochastic analysis theory, an almost sure exponential stability (ASES) criterion of the system discussed straightforwardly is developed by constructing a delay-free auxiliary system, while removing the traditional assumption of moment stability. The criterion strongly linked with topological structure, RDoS frequency, attack successful probability, and noise intensity reveals that the higher the noise intensity, the faster the convergence rate is for the stability of the network. In light of the criterion established, we present an algorithm that can be employed to analyze the tolerable attack parameters and the upper bound of the coupling delays, under the prerequisite of guaranteeing the stability of the network. Eventually, the theoretical results are applied to inertial complex-valued neural networks (ICNNs) and an illustrative example is presented to substantiate the efficiency of the theoretical works.

A passive isolation of sensor faults from un-stealthy attacks in uncertain nonlinear systems

In this paper, a novel nonlinear observer-based approach is established to cast light on the problem of isolating sensor faults from un-stealthy attacks for Lipschitz affine nonlinear systems subjected to unknown uncertainties and disturbances. A structure consisting of a multi-line transmission mechanism, a random number generator (RNG), and Dedicated Observer Scheme is developed to make the abnormal behaviors distinguishable. A group of two interlinked nonlinear Luenberger-Like observers is designed in nonlinear coordinates to detect abnormal behaviors. Two banks of detection observers and an incidence matrix are introduced to make the final decisions. Adaptive threshold techniques are exploited to guarantee the robustness against the model uncertainties and disturbances. Compared with the existing results, the proposed approach isolates the abnormal behaviors without the need for any redundant hardware components. Finally, the performance of the proposed approach is evaluated on a continuous stirred tank reactor (CSTR).

Secure State Estimation of Nonlinear Cyber-Physical Systems Against DoS Attacks: A Multiobserver Approach

This article focuses on the problem of secure state estimation for cyber-physical systems (CPSs), whose physical plants are modeled as nonlinear strict-feedback systems. The measured output is sent to the designed observer over a wireless communication network subject to denial-of-service (DoS) attacks. Due to the energy constraints of the attackers, the attack duration is upper bounded. Under DoS attacks, the transmission is prevented, which worsens the estimation accuracy of the existing nonlinear observers significantly. To maintain the estimation performance, a novel multiobserver scheme and a switched algorithm are proposed by introducing the hold-input mechanism and the cascade observer technique. In comparison to the existing results, where the estimation error systems may be unstable during the attack time interval, the estimation error of the designed observer converges exponentially, such that the estimation performance is improved effectively. Finally, the theoretical findings are illustrated by simulation results.

Injection attack estimation of networked control systems subject to hidden DoS attack

This paper is concerned with the injection attack estimation for a class of networked control systems with Deny-of-Service (DoS) attack, where unknown signals are injected into the sensor reading and actuator. The main goal is to design an estimator to estimate the injected signals subject to stochastic hidden DoS attack. By introducing a semi-Markov chain, the complex aperiodic sampling behavior caused by DoS attack is first modeled as a stochastic switching system. By using the Lyapunov stability theory and stochastic system analysis method, the σ-error mean square stability (σ-EMSS) conditions of estimation error system are then derived and the state of the attack estimation error system is shown to be uniformly ultimately bounded. Some linear matrix inequalities are proposed to determine the estimation gain matrices. Finally, both simulation and experimental studies on the motor system are conducted, and the effectiveness of the main results are demonstrated.

Secure State Estimation With Switched Compensation Mechanism Against DoS Attacks

This article is concerned with the secure state estimation problem for cyber-physical systems under intermittent denial-of-service (DoS) attacks. Based on a switching scheme and the cascade observer technique, a novel resilient state observer with a switched compensation mechanism is designed. Moreover, a quantitative relationship between the resilience against DoS attacks and the design parameters is revealed. Compared with the existing results, where only the boundedness of the estimation error is guaranteed under DoS attacks, the exponential convergence of the estimation error is achieved by employing the proposed observer scheme, such that the estimation performance is improved. More specifically, in the disturbance-free case, it is proven that the state estimation error converges exponentially to 0 despite the existence of DoS attacks. Finally, simulation results are provided to illustrate the effectiveness and merits of the proposed methods.