A federated learning framework with homomorphic encryption and dynamic agent selection detects anomalies in IIoT while preserving privacy and reducing communication bottlenecks.
Towards asynchronous federated learning for heterogeneous edge-powered internet of things,
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Towards Securing IIoT: An Innovative Privacy-Preserving Anomaly Detector Based on Federated Learning
A federated learning framework with homomorphic encryption and dynamic agent selection detects anomalies in IIoT while preserving privacy and reducing communication bottlenecks.