Active Security Control for Networked Jumping Systems Under Asynchronous Dual-Channel DoS Attacks: An HMM-Based Approach

This paper aims to address the design problem of asynchronous controllers for networked jumping systems (NJSs), in which two communication channels are vulnerable to asynchronous denial-of-service (DoS) attacks. To this end, a hidden Markov model (HMM)-based active security control strategy is proposed to counter asynchronous dual-channel DoS attacks. Firstly, two maximum consecutive numbers are introduced to describe DoS attacks randomly initiated by adversaries. Subsequently, a mode-dependent predictor is designed to generate predictive states, which can be employed in the switched controller to stabilize the NJSs. Furthermore, sufficient conditions are derived by constructing Lyapunov functions to ensure the asymptotic mean-square stability of the NJSs under asynchronous dual-channel DoS attacks. Finally, a simulation using a space robot manipulator model is presented to validate the effectiveness and practicality of the proposed active security control strategy. Note to Practitioners—This paper tackles the challenge of designing robust controllers for networked systems that are susceptible to asynchronous DoS attacks over two communication channels. In practical terms, this research is particularly relevant for systems like space robots or other critical networked infrastructures where communication interruptions can severely impact performance. The proposed solution employs an HMM-based active security control strategy to counter these attacks. The method works by predicting system states even when communication channels are compromised, allowing the controller to maintain stability and performance. This strategy is designed to handle unpredictable and random DoS attacks, which can occur independently on either communication channel. The effectiveness of this method has been validated through simulations with a space robot manipulator, highlighting its potential applicability in real-world scenarios. Although the proposed strategy shows promise, further testing in diverse operational environments is recommended to fully evaluate its reliability and scalability in practice.