Secure dynamic-event-based filtering for descriptor nonhomogeneous Markovian jump cyber-physical systems against hybrid cyber-attacks

In this article, the issue of resilient filtering for descriptor nonhomogeneous Markovian jump cyber-physical systems under hybrid cyber-attacks has been studied. First, occurrences of both deception attacks and replay attacks are modeled as two mutually independent Bernoulli distributed random variables. To depress the ratio of sampled data transmissions over the network, the dynamic version of event-triggered transmission policy is properly proposed. Then, criteria of stochastically admissible for the filtering error systems guaranteeing mixed $H_{\infty }$ and passive performance are addressed via linear matrix inequalities (LMIs). The gains of resilient filter and the dynamic event-based transmission policy can be simultaneously gained by optimizing the LMIs. Finally, two examples that include a numerical example and a direct current motor system are provided to testify the feasibility and effectiveness of the developed technique.