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SEPP-FLBC: A Secure and Efficient Privacy Protection Scheme Using Federate Learning and Blockchain for Edge-End-Cloud Devices 期刊论文
IEEE TRANSACTIONS ON SERVICES COMPUTING, 2026, 卷号: 19, 期号: 1, 页码: 657-670
作者:  Feng, Libo;  Guo, Junwei;  Fang, Fake;  He, Zhenli;  Yu, Yimin;  Yao, Shaowen;  Peng, Xiaohui
收藏  |  浏览/下载:0/0  |  提交时间:2026/05/25
Training  Federated learning  Privacy  Computational modeling  Differential privacy  Data models  Convergence  Protection  Consensus protocol  Servers  Blockchain  edge-end-cloud devices  federated learning  committee consensus  differential privacy