GHEFL: Grouping Based on Homomorphic Encryption Validates Federated Learning
Federated learning is a powerful tool for securing participants’ private data due to its ability to make data “available but not visible”. In recent years, federated learning has been enhanced by the emergence of multi-weight aggregation protocols, which minimize the impact of erroneous parameters,...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-03-01
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| Series: | Future Internet |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1999-5903/17/3/128 |
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