Adaptive privacy-preserving federated learning for robust IoT systems: A defense against data poisoning attacks
Federated Learning (FL) is a machine learning paradigm that enables collaborative model training across multiple devices, such as those found in the Internet of Things (IoT), while preserving data privacy. Despite its potential, FL is vulnerable to attacks, including data poisoning. This paper intro...
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| Hauptverfasser: | , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
KeAi Communications Co., Ltd.
2025-01-01
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| Schriftenreihe: | Internet of Things and Cyber-Physical Systems |
| Schlagworte: | |
| Online-Zugang: | http://www.sciencedirect.com/science/article/pii/S2667345226000064 |
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