Asynchronous Finite-Time Exponential Dissipative Filtering for Stochastic Fuzzy Markov Jump Systems Against Deception Attacks Based on Event-Triggered Scheme

This note aims to investigate finite-time exponential dissipative (FTED) filtering for stochastic fuzzy Markov jump systems (MJSs) subject to multiplicative noise and deception attacks. A mode-dependent event-triggered mechanism (ETM) is adopted to mitigate the pressure of network transmission, and cyber attacks are characterized in the communication channel. Besides, a hidden Markov model(HMM) is employed to describe that the system modes and filter modes are not synchronized. According to ETM and HMM, a hidden networked filtering error system model with network-induced delay and stochastic deception attacks is established. Sufficient conditions of finite-time stochastic boundedness (FTSB) are then provided for the resulting filtering error system. Furthermore, under randomly occurring deception attacks, mode-dependent event-triggered matrices and asynchronous fuzzy filter gains are co-designed, which guarantee that the filtering error system is FTSB as well as FTED. Finally, an example is presented to verify the effectiveness of obtained results.