False Data Injection Attacks Against State Estimation in Power Distribution Systems

Abstract

The existing research on false data injection (FDI) attacks against state estimation in transmission systems cannot be trivially extended to distribution feeders. The main reason is that a strong condition that requires the attacker to know the estimated state of distribution systems is needed, which makes the traditional FDI attacks difficult to be implemented in practice. In this paper, we propose a practical FDI attack model against state estimation in distribution systems, without paying expensive cost for obtaining the system state. We show that the attacker can approximate the system state based on power flow or injection measurements without too much effort. For local FDI attacks, the strong condition can be further relaxed to the knowledge of local state, which can be approximated based on a small number of power flow or injection measurements. Simulation results based on the IEEE test feeder demonstrate that the proposed practical FDI attack, even with the approximated system state, is more likely to compromise the state estimation without being detected, in comparison with the traditional attacks. This paper provides a basis to study the attack behaviors in distribution systems and a theoretical guide to develop protective countermeasures.