False-Data-Injection-Enabled Network Parameter Modifications in Power Systems: Attack and Detection

doi:10.1109/TII.2022.3172688

Return

False-Data-Injection-Enabled Network Parameter Modifications in Power Systems: Attack and Detection

2023-01-01

PRE

DOI：10.1109/TII.2022.3172688

Original

Original request for help

Save

Abstract

En 中文

Due to the close relevance to the reliability and efficiency of power systems, network parameters such as branch admittance have been the target of various cyberattacks. However, existing attack models are generally based on the impractical assumption that attackers can directly modify the data of network parameter stored in well-secured control centers. This article proposes a practical attack model and designs an optimal strategy to detect malicious modification of critical network parameters. Specifically, the vulnerability of network parameter error processing is discovered and exploited to indirectly modify the data of network parameter without accessing to the well-secured control center. A model of false-data-injection-enabled network parameter modification is proposed, which significantly reduces the requirements on attackers' capability and system information. An optimal detection strategy is designed based on the analysis of the minimal protection set at a single branch, which can significantly reduce the number of protected measurements in detecting malicious modification of critical network parameters. Finally, numerical simulations are carried out on the PJM 5-bus and the IEEE 118-bus test systems to validate the theoretical results.

Keywords:

State estimation

Power systems

Power measurement

Biological system modeling

Measurement uncertainty

Databases

Data models

False data injection (FDI) attack

indirect modifications of network parameters

optimal detection strategy

security of cyber-physical systems