A Blockchain-based federated learning framework for secure aggregation and fair incentives

Federated Learning (FL) has gained prominence as a machine learning framework incorporating privacy-preserving mechanisms. However, challenges such as poisoning attacks and free rider attacks underscore the need for advanced security measures. Therefore, this paper proposes a novel framework that in...

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Bibliographic Details

Published in:	Connection Science
Main Authors:	XiaoHui Yang, TianChang Li
Format:	Article
Language:	English
Published:	Taylor & Francis Group 2024-12-01
Subjects:	Federated learning blockchain reputation mechanism consensus poisoning attack
Online Access:	https://www.tandfonline.com/doi/10.1080/09540091.2024.2316018