This research paper investigates a protocol-based sliding mode control (SMC) approach for singularly perturbed systems with switching parameters and random occurring deception attacks. The mode switching behavior of the original system is regulated using a semi-Markov process, and a novel and more efficient mode monitoring method is proposed, distinct from the conventional hidden Markov model. Furthermore, to reduce the triggering rate while maintaining control performance, a probability-based event triggering protocol is introduced. By employing the proposed scheme along with Lyapunov theory, sufficient criteria for parameter correlation are established to ensure asymptotic stability. The designed sliding mode control incorporates a convergence factor to enhance the control performance. Finally, the feasibility and practicality of the proposed control strategy are verified through simulations using two practical models.