This article investigates the \(H_\infty \) filtering problem for networked switched Takagi–Sugeno (T-S) fuzzy systems under hybrid cyber attacks. A resilient adaptive event-triggered strategy (RAETS) is introduced to optimize communication resource utilization and mitigate attacks impacts. In contrast to the conventional adaptive mechanism, the proposed strategy not only introduces the filtering error as the trigger judgment basis, but also enables immediate data release upon cessation of attacks, thereby effectively alleviating the cumulative negative effects caused by attacks. Considering that the asynchronous switching induced by denial-of-service (DoS) attacks or network delays can significantly reduce system performance and increase the complexity of filter design, the state-dependent switching law is introduced to address these issues. Subsequently, a novel multiple Lyapunov-Krasovskii function, associated with attack signals, system modes, and filter modes, is constructed to analyze the globally uniformly exponentially stable and \(H_\infty \) performance of the switched filtering error system. Finally, an example on the single-link robot arm system is given to validate the feasibility and effectiveness of the designed filter.
