Group verifiable secure aggregate federated learning based on secret sharing
Abstract Federated learning is a distributed machine learning approach designed to tackle the problems of data silos and the security of raw data. Nevertheless, it remains susceptible to privacy leakage risks and aggregation server tampering attacks. Current privacy-preserving methods often involve...
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| Hlavní autoři: | , , , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Nature Portfolio
2025-03-01
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| Edice: | Scientific Reports |
| Témata: | |
| On-line přístup: | https://doi.org/10.1038/s41598-025-94478-0 |
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