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A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids

Musleh, Ahmed S., Chen, Guo, Dong, Zhao Yang·2020·IEEE Transactions on Smart Grid

Abstract

Cyber-physical attacks are the main substantial threats facing the utilization and development of the various smart grid technologies. Among these attacks, false data injection attack represents a main category with its widely varied types and impacts that have been extensively reported recently. In addressing this threat, several detection algorithms have been developed in the last few years. These were either model-based or data-driven algorithms. This paper provides an intensive summary of these algorithms by categorizing them and elaborating on the pros and cons of each category. The paper starts by introducing the various cyber-physical attacks along with the main reported incidents in history. The significance and the impacts of the false data injection attacks are then reported. The concluding remarks present the main criteria that should be considered in developing future detection algorithms for the false data injection attacks.

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Metadata

Authors
Musleh, A. S., Chen, G., & Dong, Z. Y.
Venue
IEEE Transactions on Smart Grid
Published
2020-05
Volume
11
Issue
3
Pages
2218-2234
ISSN
  • 1949-3053 (ISSN-L)
  • 1949-3061
OpenAlex
W2984195658
Cited by
714
References
2
FWCI
33.44
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids. https://app.cochat.ai/papers/10.1109/tsg.2019.2949998
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Musleh, A. S., Chen, G., & Dong, Z. Y. (2020). A Survey on the Detection Algorithms for False Data Injection Attacks in Smart Grids. IEEE Transactions on Smart Grid. https://doi.org/10.1109/tsg.2019.2949998

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.