A Two-Stage Hybrid Federated Learning Framework for Privacy-Preserving IoT Anomaly Detection and Classification

The rapid surge of Artificial Internet-of-Things (AIoT) devices has outpaced the deployment of robust, privacy-preserving anomaly detection solutions suitable for resource-constrained edge environments. This paper presents a two-stage hybrid Federated Learning (FL) framework for IoT anomaly detectio...

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Bibliographic Details

Published in:	IoT
Main Authors:	Mohammad Shahin, Ali Hosseinzadeh, F. Frank Chen
Format:	Article
Language:	English
Published:	MDPI AG 2025-08-01
Subjects:	AIoT generative AI variational autoencoder anomaly detection sustainable manufacturing cyber security
Online Access:	https://www.mdpi.com/2624-831X/6/3/48