Studying cyber attack-defense interaction over load frequency control (LFC) had become critical for guaranteeing the frequency quality and safety operation of power systems. It was revealed that both the attacker and the defender have multiple alternatives from strategy pools, which results in optimal strategy selection in pursuit of optimal payoff. In this paper, game theory model is introduced to analyze optimal strategy of attack-defense interaction over LFC. As to payoff calculation, we consider the comprehensive evaluating metric containing both the application effect and implementation cost of specific strategies, and propose a fuzzy logic-based calculation method. Considering the incomplete information in the attack-defense interaction game, we propose a mixed strategy method to obtain the optimal strategy. The simulation results show the effectiveness of the proposed optimal strategies. INDEX TERMS Load frequency control, attack-defense interaction, optimal strategy, zero-sum game, incomplete information.

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Cyber attacks bring key challenges to the system reliability of load frequency control (LFC) systems. Attackers can compromise the measured data of critical variables of the LFC system, making the data received by the defender unreliable and resulting in system frequency fluctuation or even collapse. In this paper, to detect potential attacks on measured data, we propose a novel attack detection scheme using the dual-source data (DSD) of compromised variables. First, we study the characteristics of the compromised LFC system considering potentially vulnerable variables and different types of attack templates. Second, by designing a variable observer, the relationship between the known security variables and the variables which are at risk of being compromised in the LFC system is established. The features of the data obtained by the observer can reflect those of the true data. Third, a Siamese network (SN) is designed to quantify the distance between the characteristics of measured data and that of observed data. Finally, an attack detection scheme is designed by analyzing the similarity of the DSD. Simulation results verify the feasibility of the detection scheme studied in this paper.