A federated spatiotemporal graph model detects passive attacks in smart grids at 98.32% per-timestep accuracy on a synthetic heterogeneous dataset using ego-centric graph convolutions and bidirectional GRUs.
Smart Grid Cyber Attacks Detection Using Supervised Learning And Heuristic Feature Selection,
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Federated Spatiotemporal Graph Learning for Passive Attack Detection in Smart Grids
A federated spatiotemporal graph model detects passive attacks in smart grids at 98.32% per-timestep accuracy on a synthetic heterogeneous dataset using ego-centric graph convolutions and bidirectional GRUs.