Federated Learning for Distributed IoT Security: A Privacy-Preserving Approach to Intrusion Detection

Federated Learning for Distributed IoT Security: A Privacy-Preserving Approach to Intrusion Detection

Billions of resource-constrained IoT devices now stream security-critical yet privacy-sensitive traffic across the Internet. To detect intrusions without exposing raw data, we propose a federated learning (FL) framework that trains collaboratively on the edge while preserving privacy. At its core is...

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Bibliographic Details
Main Authors: Chandu Gutti, Karthik Thumula, Parag Balbudhe
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Federated learning
IoT security
intrusion detection system
privacy-preserving
distributed learning
cybersecurity
Online Access:https://ieeexplore.ieee.org/document/11095679/
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https://ieeexplore.ieee.org/document/11095679/

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