In the paper, the scheme of robust \(H_{\infty }\) filtering for discrete-time nonlinear networked systems (NNSs) based on an adaptive event-triggered scheme (AETS) is proposed. Firstly, the Takagi–Sugeno (T–S) fuzzy model is used to approximate the NNSs. In addition, based on the network environment where deception attacks occur randomly, the \(H_{\infty }\) filtering design strategy of multi-channel deception attacks based on Bernoulli binomial distribution is studied. To further reduce the network burden, an improved multi-channel AETSs is introduced to reduce the transmission of network data. Then, the design conditions of \(H_{\infty }\) filtering are described by strict linear matrix inequalities (LMIs), such that the filtering error system satisfies mean-square asymptotic stability and the prescribed given \(H_{\infty }\) performance is guaranteed. Finally, two simulation examples of tunnel diode circuit and permanent magnetic synchronous generator illustrate the availability and superiority of the designed method.
