The increasing risk of cyber-physical attacks (CPAs) on power infrastructure has led to need for reliable detection technologies. As the landscape of cyber threats evolves, it becomes imperative to continually update and enhance attack detection techniques. This research investigates the formulation of detection algorithm, via combination of State Partition Particle Filter (SP-PF) theories for power system security. The proposed approach applies intelligent partitioning of the state space so as to be accurately represented with fewer particles. This reduction in computational demand enhances the algorithm’s efficiency, making it more practical for real-time applications. The detection algorithm based on SP-PF is tested against switching attacks (SAs) launched on the governor and excitation systems associated with the generator. The RTDS platform is utilized for conducting real-time simulations of IEEE 9-bus power network in order to demonstrate the efficacy of proposed SP-PF based detection SA in real-time.