A Blockchain-based federated learning framework for secure aggregation and fair incentives
Federated Learning (FL) has gained prominence as a machine learning framework incorporating privacy-preserving mechanisms. However, challenges such as poisoning attacks and free rider attacks underscore the need for advanced security measures. Therefore, this paper proposes a novel framework that in...
| Published in: | Connection Science |
|---|---|
| Main Authors: | XiaoHui Yang, TianChang Li |
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
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| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/09540091.2024.2316018 |
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