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In recent years, cyber-security of power systems has become a growingconcern. To protect power systems from malicious adversaries, advanced defensestrategies that exploit sophisticated detection algorithms are required.Motivated by this, in this paper we introduce an active defense method based ondynamic clustering. Our detection strategy uses a moving-target approach whereinformation about the system's varying operating point is first used to clustermeasurements according to their transfer function characteristics that changeover time. Then, detection is carried out through series of similarity checksbetween measurements within the same cluster. The proposed method is effectivein detecting cyber-attacks even when the attacker has extensive knowledge ofthe system parameters, model and detection policy at some point in time. Theeffectiveness of our proposed detection algorithm is demonstrated through anumerical example on the IEEE 24-bus power system.

A Moving-target Cyber-Attack Detection Strategy for Large-scale Power Systems using Dynamic Clustering