Federated learning with differential privacy via fast Fourier transform for tighter-efficient combining

Abstract Spurred by the simultaneous need for data privacy protection and data sharing, federated learning (FL) has been proposed. However, it still poses a risk of privacy leakage in it. This paper, an improved Differential Privacy (DP) algorithm to protect the federated learning model. Additionall...

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Bibliographic Details
Main Authors: Shengnan Guo, Jianfeng Yang, Shigong Long, Xibin Wang, Guangyuan Liu
Format: Article
Language:English
Published: Nature Portfolio 2024-11-01
Series:Scientific Reports
Subjects:
Online Access:https://doi.org/10.1038/s41598-024-77428-0
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