A Bayesian Game-Theoretic Defense Strategy for False Data Injection Attacks in Smart Grid

Abstract

Smart grid security has been the subject of substantial research and many techniques have been proposed for the modeling and analysis of the myriad types of attack-defense scenarios that could play out on various sections of the smart grid. Of these, the false data injection attack (FDIA) on the state estimator has received considerable attention. In this paper, the attack and detection stages of the FDIA on the smart grid are modeled as a Bayesian security game. The main contribution of this paper lies in the development of a Bayesian Nodal Analysis for the calculation of a critical set of meters to be defended in case of an FDIA. The proposed model also validates the edge of the Aberration Index metric over the residues for the detection of FDIA in the smart grid.