Abstract: This paper presents a hybrid event-triggered synchronous control method for a master-slave neural network subject to deception attacks. The proposed method employs a hybrid event-triggered scheme based on Bernoulli distribution to reduce the communication burden and handle the unpredictable network environment by transmitting data only when necessary. Notably, the memory event trigger mechanism can transmit more data during the peak and bottom of the system’s response state. To account for uncertainties in the system, including network-induced delay and randomly occurring deception attacks are developed within a unified framework and the corresponding Lyapunov-Krasovskii functional (LKF) is constructed. A stabilization criterion is then derived using Lyapunov theory. Numerical simulations demonstrate the effectiveness of the proposed method.