On PMU Data Integrity under GPS Spoofing Attacks: A Sparse Error Correction Framework

TL;DR

This paper introduces a sparse error correction framework to identify and mitigate GPS spoofing attacks on PMU data, leveraging network topology and PMU placement to enhance data integrity in power systems.

Contribution

The paper proposes a novel sparse error correction method for PMU data under GPS spoofing, including attack identifiability conditions and a scalable correction approach.

Findings

Effective correction of spoofed PMU data demonstrated in simulations

Identifiability conditions depend on network topology and PMU placement

Scalable zone-based computation improves correction efficiency

Abstract

Consider the problem of mitigating the impact on data integrity of phasor measurement units (PMUs) given a GPS spoofing attack. We present a sparse error correction framework to treat PMU measurements that are potentially corrupted due to a GPS spoofing attack. We exploit the sparse nature of a GPS spoofing attack, which is that only a small fraction of PMUs are affected by the attack. We first present attack identifiability conditions (in terms of network topology, PMU locations, and the number of spoofed PMUs) under which data manipulation by the spoofing attack is identifiable. The identifiability conditions have important implications on how the locations of PMUs affect their resilience to GPS spoofing attacks. To effectively correct spoofed PMU data, we present a sparse error correction approach wherein computation tasks are decomposed into smaller zones to ensure scalability. We present experimental results obtained from numerical simulations with the IEEE RTS-96 and IEEE 300 test networks to demonstrate the effectiveness of the proposed approach.