Interacting multiple model estimator for event-triggered cyber-physical systems against Denial-of-service attacks

This paper investigates the problem of security state estimation of event-triggered cyber-physical systems (CPSs) under constrained bandwidth and random DoS attacks. Two independent Markov chains are introduced to separately describe the transition of system models and the occurrence of DoS attacks. By presenting an event-triggered scheduling mechanism based on the measurement innovation, the impact of bandwidth and power limitations in CPSs is mitigated. For the purpose of reducing the complexity of model sequences, the interacting multiple model (IMM) framework is extended event-triggered CPSs to cut down the the branch of exponential growth assumptions. In addition, the statistical information of event-triggered conditions are utilized to estimate the continuous state, identify the system mode and detect DoS attacks. Finally, the performance of the proposed method is validated by Monte Carlo simulation in a two-dimensional maneuvering target tracking.