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Cited by 553

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False Data Injection on State Estimation in Power Systems—Attacks, Impacts, and Defense: A Survey

Deng, Ruilong, Xiao, Gaoxi, Lu, Rongxing, Liang, Hao, Vasilakos, Athanasios V.·2017·IEEE Transactions on Industrial Informatics

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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Metadata

Authors
Deng, R., Xiao, G., Lu, R., Liang, H., & Vasilakos, A. V.
Venue
IEEE Transactions on Industrial Informatics
Published
2017-04
Volume
13
Issue
2
Pages
411-423
ISSN
  • 1551-3203 (ISSN-L)
  • 1941-0050
OpenAlex
W2525022545
Cited by
553
References
3
FWCI
33.11
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: False Data Injection on State Estimation in Power Systems—Attacks, Impacts, and Defense: A Survey. https://app.cochat.ai/papers/10.1109/tii.2016.2614396
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Deng, R., Xiao, G., Lu, R., Liang, H., & Vasilakos, A. V. (2017). False Data Injection on State Estimation in Power Systems—Attacks, Impacts, and Defense: A Survey. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2016.2614396

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