Mitigating False-data Injection Attacks on DC State Estimation using Covert Topological Information

Abstract

A well-functioning power system relies on its accurate state estimation. However, recent research shows that well-structured false-data injection attacks can bypass the current security system and introduce arbitrary errors to state estimates. In this paper, we propose a novel defending mechanism against false-data injection attacks using covert power network topological information. By keeping the exact reactance of a set of transmission lines from attackers, no false data injection attack can be launched to compromise any set of critical state estimates. We first investigate from the attackers' perspective the necessary condition to perform injection attack. Based on the arguments, we characterize the optimal protection problem, which protects the state estimates with minimum number of covert transmission lines, into a minimum Steiner tree problem in a graph, where some off-the-shelf algorithms can be applied. Besides, we also propose a mixed defending strategy that jointly considers the use of covert topological information (CTI) and secure meter measurements when CTI protection alone fails to achieve the protection objective due to technical constraints. The advantageous performance of the proposed defending mechanisms is verified in IEEE standard power system testcase. Our results here will be useful in the security upgrade projects of large-scale electrical power system towards smart power grids.