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  • Deng, Ruilong, et al. (author)
  • False Data Injection on State Estimation in Power Systems—Attacks, Impacts, and Defense: A Survey
  • 2017
  • In: IEEE Transactions on Industrial Informatics. - : IEEE. - 1551-3203 .- 1941-0050. ; 13:2, s. 411-423
  • Journal article (peer-reviewed)abstract
    • The accurately estimated state is of great importance for maintaining a stable running condition of power systems. To maintain the accuracy of the estimated state, bad data detection (BDD) is utilized by power systems to get rid of erroneous measurements due to meter failures or outside attacks. However, false data injection (FDI) attacks, as recently revealed, can circumvent BDD and insert any bias into the value of the estimated state. Continuous works on constructing and/or protecting power systems from such attacks have been done in recent years. This survey comprehensively overviews three major aspects: constructing FDI attacks; impacts of FDI attacks on electricity market; and defending against FDI attacks. Specifically, we first explore the problem of constructing FDI attacks, and further show their associated impacts on electricity market operations, from the adversary's point of view. Then, from the perspective of the system operator, we present countermeasures against FDI attacks. We also outline the future research directions and potential challenges based on the above overview, in the context of FDI attacks, impacts, and defense.
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Type of publication
journal article (1)
Type of content
peer-reviewed (1)
Author/Editor
Vasilakos, Athanasio ... (1)
Liang, Hao (1)
Deng, Ruilong (1)
Xiao, Gaoxi (1)
Lu, Rongxing (1)
University
Luleå University of Technology (1)
Language
English (1)
Research subject (UKÄ/SCB)
Natural sciences (1)
Year

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