Event-Triggered H∞ Filtering for Networked Systems Under Hybrid Probability Deception Attacks

In this article, the deception attacks are the research object, which are widely concerned in cyber attacks, and the feasibility of
$H_\infty $
filtering for networked system based on event-triggered mechanism (ETM) is discussed. Firstly, in order to avoid waste of limited bandwidth, the ETM are introduced. At the same time, considering the impact of two types of different deception attacks, we introduce respectively two sets of random variables satisfying the Bernoulli distribution to depict the probability of the data transmitted by the network being subjected to deception attacks and the switching law of two types of deception attacks. Furthermore, a function model in accordance with the above situation is established. Then, by using Lyapunov-Krasovskii functional (LKF) and linear matrix inequalities (LMIs) techniques, the stability criterion of the established system model and the display expression of filter parameters are obtained. For the single integral terms in the derivative of LKF, we utilize Jensen’s Inequality and reciprocally convex combination lemma (RCCL) to process them. Finally, the feasibility of the proposed method is verified by a simulation example.