Security Threat Analytics and Countermeasure Synthesis for Power System State Estimation

Abstract

State estimation plays a critically important role in ensuring the secure and reliable operation of the power grid. However, recent works have shown that the widely used weighted least squares (WLS) estimator, which uses several system wide measurements, is vulnerable to cyber attacks wherein an adversary can alter certain measurements to corrupt the estimator's solution, but evade the estimator's existing bad data detection algorithms and thus remain invisible to the system operator. Realistically, such a stealthy attack in its most general form has several constraints, particularly in terms of an adversary's knowledge and resources for achieving a desired attack outcome. In this light, we present a formal framework to systematically investigate the feasibility of stealthy attacks considering constraints of the adversary. In addition, unlike prior works, our approach allows the modeling of attacks on topology mappings, where an adversary can drastically strengthen stealthy attacks by intentionally introducing topology errors. Moreover, we show that this framework allows an operator to synthesize cost-effective countermeasures based on given resource constraints and security requirements in order to resist stealthy attacks. The proposed approach is illustrated on standard IEEE test cases.