通信学报2024，Vol.45Issue(4)：201-215,15.DOI:10.11959/j.issn.1000-436x.2024072
基于多级代理许可区块链的联邦边缘学习模型
Federated edge learning model based on multi-level proxy per-missioned blockchain
摘要
Abstract
Aiming at the problems of privacy security and low learning efficiency faced by federated learning in zero trust edge computing environment,a federated learning model based on multi-level proxy permission blockchain for edge computing was proposed.The multi-level proxy permission blockchain was designed to establish a trusted underly-ing environment for federated edge learning,and the hierarchical model aggregation scheme was implemented to allevi-ate the pressure of model training.A hybrid strategy was devised to enhance model privacy using secret sharing and dif-ferential privacy.A federated task node selection algorithm based on reputation verification was devised to address the problem of zero or extremely poor credibility of edge clients.Positive training samples and the local model were utilized as reputation rewards to refine the security verification scheme,and further ensure the effectiveness of the model against malicious adversaries.Experimental results show that under the attack of 40%malicious adversaries,compared with the existing advanced schemes,the accuracy of the proposed scheme is improved by 10%,and high privacy security is achieved with high model accuracy.关键词
联邦学习/区块链/数据安全/隐私保护/边缘计算Key words
federated learning/blockchain/data security/privacy-preserving/edge computing分类
信息技术与安全科学引用本文复制引用
葛丽娜,栗海澳,王捷..基于多级代理许可区块链的联邦边缘学习模型[J].通信学报,2024,45(4):201-215,15.基金项目
国家自然科学基金资助项目(No.61862007) （No.61862007）
广西自然科学基金资助项目(No.2020GXNSFBA297103)The National Natural Science Foundation of China(No.61862007),Guangxi Natural Science Foundation(No.2020GXNSFBA297103) （No.2020GXNSFBA297103）
