PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity

PPFL-DCS: Privacy-Preserving Federated Learning Using Neural Transformer and Leveraging Dynamic Client Selection to Accommodate Data Diversity

The vulnerabilities and security issues of industrial Cyber-Physical Systems (CPSs), such as Intrusion Detection Systems (IDSs), have significantly increased due to the rapid integration of conventional industrial setups with advanced networking and computing technologies like 5G, software-defined n...

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Bibliographic Details
Main Authors: Nakul Mehta, Nitesh Bharot, John G. Breslin, Priyanka Verma
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Industry 4.0
intrusion detection system
federated learning
stacked AutoEncoders
cyber threats
membership inference attacks
Online Access:https://ieeexplore.ieee.org/document/11009015/
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https://ieeexplore.ieee.org/document/11009015/

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