Springer Nature OA
open access
CC BY 4.0
Synthetic false data injection-inspired perturbation framework for power grid attack detection using graph neural networks and deep learning models
Modern power grids are exposed to False Data Injection (FDI) attacks due to their increasing dependency on digital sensing and measurement infrastructure. The adversaries deliberately manipulate sensor data for compromising control, system monitoring, and overall grid stability. Undetected attacks t
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