A correlation analysis-based federated learning framework for defending against collusion-free-riding attacks

Abstract Federated learning (FL) is a type of distributed machine learning that enables multiple participants to collaboratively build machine learning models without transferring data outside their local devices, thereby ensuring data privacy and security. However, free-riding (FR) attacks pose sig...

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Bibliographic Details

Published in:	Cybersecurity
Main Authors:	MeiTing Xue, Hao Zhong, Yukun Shi, Yan Zeng, Jilin Zhang, Nailiang Zhao
Format:	Article
Language:	English
Published:	SpringerOpen 2025-09-01
Subjects:	Federated learning Privacy protection Collusion-based FR attacks Non-IID
Online Access:	https://doi.org/10.1186/s42400-025-00366-5