4.8 Article

On Feasibility and Limitations of Detecting False Data Injection Attacks on Power Grid State Estimation Using D-FACTS Devices

期刊

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 16, 期 2, 页码 854-864

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2019.2922215

关键词

Distributed flexible ac transmission system (D-FACTS) devices; false data injection (FDI) attacks; state estimation; feasibility and limitations; smart grids

资金

  1. National Key Research and Development Program of China [2016YFB08006004, 2016YFB08006005]
  2. National Natural Science Foundation of China [61872255, U1736212, 61572334]
  3. Fundamental Research Funds for the Central Universities, Sichuan University [YJ201933]
  4. Ministry of Education, Singapore [MOE2016-T2-1-119]
  5. Future Resilient System Project at the Singapore-ETH Centre - National Research Foundation of Singapore
  6. Nanyang Technological University (NTU) [M4082287]
  7. A*STAR-NTU-SUTD AI Partnership [RGANS1906]
  8. Natural Science Foundation of Zhejiang Province [LY17F020006]
  9. Key Research and Development Program of Science and Technology Department of Zhejiang Province [2017C01015]

向作者/读者索取更多资源

Recent studies have investigated the possibilities of proactively detecting the high-profile false data injection (FDI) attacks on power grid state estimation by using the distributed flexible ac transmission system (D-FACTS) devices, termed as proactive false data detection (PFDD) approach. However, the feasibility and limitations of such an approach have not been systematically studied in the existing literature. In this paper, we explore the feasibility and limitations of adopting the PFDD approach to thwart FDI attacks on power grid state estimation. Specifically, we thoroughly study the feasibility of using PFDD to detect FDI attacks by considering single-bus, uncoordinated multiplebus, and coordinatedmultiple-bus FDI attacks, respectively. We prove that PFDD can detect all these three types of FDI attacks targeted on buses or super-buses with degrees larger than 1, if and only if the deployment of D-FACTS devices covers branches at least containing a spanning tree of the grid graph. The minimum efforts required for activating D-FACTS devices to detect each type of FDI attacks are, respectively, evaluated. In addition, we also discuss the limitations of this approach; it is strictly proved that PFDD is not able to detect FDI attacks targeted on buses or super-buses with degrees equalling 1.

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