FL-AGN: A Privacy-Enhanced Federated Learning Method Based on Adaptive Gaussian Noise for Resisting Gradient Inference Attacks
As well-known, the paradigm of federated learning (FL) operates on the principle that without centralizing data into a single server, server only trains and updates global models based on the local model from multiple clients. Compared with traditional machine learning, FL enables that data availabi...
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| Główni autorzy: | , , |
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| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
IEEE
2024-01-01
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| Seria: | IEEE Access |
| Hasła przedmiotowe: | |
| Dostęp online: | https://ieeexplore.ieee.org/document/10604811/ |
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