Cyber Attack Detection Scheme for a Load Frequency Control System Based on Dual-Source Data of Compromised Variables

Abstract

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.