Privacy-Preserving Federated Learning Using Homomorphic Encryption

Federated learning (FL) is a machine learning technique that enables distributed devices to train a learning model collaboratively without sharing their local data. FL-based systems can achieve much stronger privacy preservation since the distributed devices deliver only local model parameters train...

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Bibliographic Details

Published in:	Applied Sciences
Main Authors:	Jaehyoung Park, Hyuk Lim
Format:	Article
Language:	English
Published:	MDPI AG 2022-01-01
Subjects:	privacy preserving homomorphic encryption federated learning
Online Access:	https://www.mdpi.com/2076-3417/12/2/734