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Quick and accurate detection of cyber attack is key to the normal operationof the smart grid system. In this paper, a joint state estimation andsequential attack detection method for a given bus with grid frequency drift isproposed that utilizes the commonly monitored output voltage. In particular,based on a non-linear state-space model derived from the three-phase sinusoidalvoltage equations, we employ the sequential Monte Carlo (SMC) filtering toestimate the system state. The output of the SMC filter is fed into a CUSUMtest to detect the attack in a fastest way. Moreover, an adaptive samplingstrategy is proposed to reduce the rate of taking measurements andcommunicating with the controller. Extensive simulation results demonstratethat the proposed method achieves high adaptivity and efficient detection ofvarious types of attacks in power systems.

Quickest Attack Detection in Smart Grid Based on Sequential Monte Carlo Filtering