This article considers a cyber-physical system with multiple remote state estimation subsystems under denial-of-service (DoS) attack. Suppose that there are multiple distributed estimation systems, in each of which, a sensor monitors the system and sends its local estimation to a remote estimator over one of multiple wireless channels. A DoS attacker emits noise power to jam the wireless channels. A scheduler is installed to dispatch each sensor to transmit information through the specific channel to minimize the total estimation error covariance on account of energy-saving. Whereas, the DoS attacker attempts to jam a channel to realize an opposite objective. With considering interference from other individuals, a multisensor multichannel remote state estimation model is constructed. A myopic policy and a long-term online interaction strategy under varying network environment are investigated and compared by solving a two-player zero-sum game and a Markov game, respectively. Simulations are provided to demonstrate our results.

The resilient control refers to the control methodology which provides an interdisciplinary solution to secure the control system. In this paper, the resilient control problem is investigated for a class of wireless networked control systems (WNCS) under a denial-of-service (DoS) attack. In the presence of the DoS attacker, the control command sent by the transmitter may be interfered, which can cause the degradation of the signal-to-interference-plus-noise ratio and further lead to packet dropout phenomenon. Such a packet dropout phenomenon is described by a two-state Markov-chain. A cross-layer view is adopted toward the security issue of the considered WNCS. The Nash power strategies and optimal control strategy in the delta-domain are obtained in the cyber- and physical-layer, respectively. Based on the obtained strategies, the coupled-design problem is solved which aims to drive the underlying control performance to the desired security region by dynamically manipulating the cyber-layer pricing parameters. Finally, a numerical simulation is conducted to verify the validity of the proposed methodology.

In this paper, the security problem for a cloud control system (CCS) is studied. In the CCS, so-called advanced persistent threats (APTs) can be launched by a malicious attacker to reduce the quality of service of cloud and deteriorate the system performance further. To defend against APTs and create a security as a service scheme, a defender needs to allocate defense resource to different units serving to different plants for improving the overall system performance when the CCS accommodates multiple physical plants simultaneously. After observing the defender's action, the attacker decides which serve units to comprise. Considering that both defender and attacker are subject to resource constraints, the interaction of two sides is modeled by a Stackelberg game. The optimal solutions for two players under different types of budget constraints are investigated. Simulation examples and comparison results are provided to verify the main results of this paper.

In this article, the primary focus is on studying a Nash equilibrium (NE) seeking algorithm to maintain system resilience in multi-agent systems (MASs), which are subject to denial-of-service (DoS) attacks and disturbance. Furthermore, we demonstrate the performance of the algorithm in tolerating such attacks. DoS attacks are modeled using Markov processes, and their impact on interagent communication is investigated. The considered n-order MAS is unable to maintain normal communication links when subjected to DoS attacks. To address this issue, stability analysis is conducted to demonstrate the effectiveness of the proposed NE seeking algorithm in achieving secure control of MAS. Conditions for maintaining resilience under attacks are also provided. Finally, numerical simulations are performed on a satellite cluster system, and physical experiments are conducted using a wheeled robot ground platform to validate the effectiveness of the algorithm.