Security‐based fault detection filtering design for fuzzy singular semi‐Markovian jump systems via improved dynamic event‐triggering and quantization protocols

Abstract

SummaryThis article concerns the problem of event‐protocol‐based asynchronous fault detection filtering design for discrete‐time fuzzy singular semi‐Markovian jump systems subjected to system parameters uncertainties, unmatched one‐sided Lipschitz nonlinearities and multi‐cyber‐attacks. First, a well‐designed model structure is proposed to integrate two dynamic quantizers and an improved dynamic event‐triggered protocol into a unified framework to reduce the amount of data in the network transmission and rationalize the use of limited network communication bandwidth resources. Especially, the event‐triggering threshold parameter can be continuously adjusted over the time based on the fluctuation of the network signal. Second, a novel triple‐cyber‐attacks platform is established, of which including random deception attacks, random replay attacks and aperiodic DoS attacks. And with help of the extended decoupling strategy and iterative techniques, the co‐design conditions of the stochastic admissibility with a level of performance are derived for the fault filtering error systems. Finally, two examples are provided to demonstrate the effectiveness and feasibility of the proposed algorithm.

Network Information Security Monitoring Under Artificial Intelligence Environment

“…Network attack detection is the primary concern for NIS, and the resulting network attack detection systems are diverse, such as open-source HIDS security, Snort, Huawei NIP series intrusion detection system, Venustech IDS, and NSFOCUS NIDS, all with their own characteristics (Kong et al, 2024).…”