Secure aggregation for semi-decentralized federated learning under heterogeneous data
Semi-decentralized federated learning has gained attention for combining the advantages of centralized and decentralized approaches, thereby enhancing system scalability and flexibility. However, in the open heterogeneous federated learning architecture, the existence of semi-honest participants and...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
POSTS&TELECOM PRESS Co., LTD
2025-06-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2025029 |
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