Ruby D
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2026
In-network Attack Detection with Federated Deep Learning in IoT Networks: Real Implementation and Analysis
This paper proposes and evaluates a federated deep learning framework using autoencoders for lightweight, privacy-preserving, and scalable real-time anomaly detection in resource-constrained IoT networks.
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