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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Main Authors: | , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2024-11-01
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Series: | Scientific Reports |
Subjects: | |
Online Access: | https://doi.org/10.1038/s41598-024-77428-0 |
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