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Blockchain-Enabled Federated Learning with Knowledge Distillation for Intrusion Detection
Published on 2025-02-17 by Mohammed Shalan, Md Rakibul Hasan, Yan Bai, Juan Li @MDPI
Abstract: The increasing adoption of smart home devices has raised significant concerns regarding privacy, security, and vulnerability to cyber threats. This study addresses these challenges by presenting a federated learning framework enhanced with blockchain technology to detect intrusions in smart home environments. The proposed approach combines knowledge distillation and transfer learning to support heterogeneous IoT devices with varying computational capacities, ensuring efficient local training wit[...]
Our summary: Study presents a blockchain-enabled federated learning framework for detecting intrusions in smart home environments. The approach combines knowledge distillation and transfer learning to support heterogeneous IoT devices, ensuring efficient local training without compromising privacy. Results show significant improvements in intrusion detection accuracy, particularly for resource-constrained devices.
Blockchain, Federated Learning, Knowledge Distillation, Intrusion Detection
Publication
