Emergent Mind

Abstract

Recent attacks on power grids demonstrated the vulnerability of the grids to cyber and physical attacks. To analyze this vulnerability, we study cyber-physical attacks that affect both the power grid physical infrastructure and its underlying Supervisory Control And Data Acquisition (SCADA) system. We assume that an adversary attacks an area by: (i) disconnecting some lines within that area, and (ii) obstructing the information (e.g., status of the lines and voltage measurements) from within the area to reach the control center. We leverage the algebraic properties of the AC power flows to introduce the efficient EXPOSE Algorithm for detecting line failures and recovering voltages inside that attacked area after such an attack. The EXPOSE Algorithm outperforms the state-of-the-art algorithm for detecting line failures using partial information under the AC power flow model in terms of scalability and accuracy. The main advantages of the EXPOSE Algorithm are that its running time is independent of the size of the grid and number of line failures, and that it provides accurate information recovery under some conditions on the attacked area. Moreover, it approximately recovers the information and provides the confidence of the solution when these conditions do not hold.

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