Local Load Redistribution Attacks in Power Systems With Incomplete Network Information

TLDR

Power grids are critical infrastructure vulnerable to cyber attacks, and although false data injection requires full network knowledge, attackers can still compromise systems even when only partial topology and parameter information is available. This study proposes a local load‑redistribution attack model that demonstrates how an adversary can inject undetected false data using only the network information of a targeted local region. The model relies on locally available topology and parameter data to generate false meter readings that bypass the state estimator’s residue test within the attack region. Simulations on a modified IEEE 14‑bus system confirm the model’s effectiveness and illustrate the attack mechanism’s implications for the complexity of defending power systems against false data injection.

Abstract

Power grid is one of the most critical infrastructures in a nation and could suffer a variety of cyber attacks. Recent studies have shown that an attacker can inject pre-determined false data into smart meters such that it can pass the residue test of conventional state estimator. However, the calculation of the false data vector relies on the network (topology and parameter) information of the entire grid. In practice, it is impossible for an attacker to obtain all network information of a power grid. Unfortunately, this does not make power systems immune to false data injection attacks. In this paper, we propose a local load redistribution attacking model based on incomplete network information and show that an attacker only needs to obtain the network information of the local attacking region to inject false data into smart meters in the local region without being detected by the state estimator. Simulations on the modified IEEE 14-bus system demonstrate the correctness and effectiveness of the proposed model. The results of this paper reveal the mechanism of local false data injection attacks and highlight the importance and complexity of defending power systems against false data injection attacks.