Federated Learning for Distributed Anomaly Detection in Network Traffic Using GRU-Based Models - Hamad Riaz; Muhammad Zunnurain Hussain; Muhammad Zulkifl Hasan; Muzzamil Mustafa (Spectrum of Engineering Sciences, 2025)
In this work, we present a novel machine learning method for anomaly detection in network traffic based on GRU based federated learning. Our decentralized method is supported by extensive experimental results and comparisons with existing techniques, and successfully addresses scenarios where centralized servers are not feasible due to privacy concerns or other constraints, and successfully detects anomalies in the distributed environments..