Confidence-aware collaborative detection mechanism for false data attacks in smart grids

Nowadays, the false data injection attack (FDIA), which can bring inestimable losses to smart grids, has become one of the most threatening cyber attacks in cyber physical systems. Previous studies for false data detection focused on state estimation, which require a huge computational overhead at the control center. In this paper, we propose a confidence-aware collaborative detection mechanism for false data attacks, which is a fast and lightweight scheme. Firstly, we propose a trust-based compromised PMU identification method, in order to identify malicious PMUs by monitoring behaviors of PMUs in a cycle. Secondly, we propose a voting-based detection method based on physical rules, in order to detect FDIA collaboratively. This method improves the detection rate while reducing the computational cost at control center. We also make extensive experiments on real-time data that are collected from the PowerWorld simulator. The experimental results show the efficiency and effectiveness of our proposed mechanism and methods.

Automated summary

This paper proposes a confidence-aware collaborative detection mechanism for false data attacks, including trust-based compromised PMU identification and voting-based detection method based on physical rules, which can improve the detection rate of false data attacks and reduce the computational cost at the control center.