Targeted False Data Injection Attack against DC State Estimation without Line Parameters

TL;DR

This paper introduces a new false data injection attack method against DC state estimation that does not require network parameters and can target specific states using limited PMU data, successfully bypassing detection.

Contribution

It presents a novel FDIA model that operates without line parameters and demonstrates high success rates in bypassing bad data detection in simulated systems.

Findings

Achieves up to 95.3% success rate in bypassing BDD.

Operates without requiring network line parameters.

Effective in targeting specific states using limited PMU data.

Abstract

A novel false data injection attack (FDIA) model against DC state estimation is proposed, which requires no network parameters and exploits only limited phasor measurement unit (PMU) data. The proposed FDIA model can target specific states and launch large deviation attacks using estimated line parameters. Sufficient conditions for the proposed method are also presented. Different attack vectors are studied in the IEEE 39-bus system, showing that the proposed FDIA method can successfully bypass the bad data detection (BDD) with high success rates of up to 95.3%.