A Comprehensive Survey on the Usage of Machine Learning to Detect False Data Injection Attacks in Smart Grids
This article provides a comprehensive survey on the application of machine learning techniques for detecting False Data Injection Attacks (FDIA) in smart grids. It introduces a novel taxonomy categorizing detection methods based on key criteria such as AC and DC systems, performance metrics, bus siz...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Computer Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11063250/ |
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