| 基于信誉评估机制和区块链的移动网络联邦学习方案 |
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| 作者姓名： | 杨明 胡学先 张启慧 魏江宏 刘文芬 |
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| 作者单位： | 1. 信息工程大学，河南 郑州 450001;2. 桂林电子科技大学，广西 桂林541004 |
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| 基金项目： | 国家自然科学基金(62172433);国家自然科学基金(62172434);国家自然科学基金(61862011);国家自然科学基金(61872449);广西密码学与信息安全重点实验室研究课题(GCIS201704) |
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| 摘 要： | 联邦学习是一种新兴的分布式机器学习技术，通过将训练任务下放到用户端，仅将训练得到的模型参数发送给服务端，整个过程并不需要参与方直接共享数据，从而很大限度上规避了隐私问题。然而，这种学习模式中移动用户间没有预先建立信任关系，用户之间进行合作训练时会存在安全隐患。针对上述问题，提出一种基于信誉评估机制和区块链的移动网络联邦学习方案，该方案允许服务端利用主观逻辑模型对参与训练的移动用户进行信誉评估，并且基于区块链智能合约技术为其提供可信的信誉意见共享环境和动态访问策略接口。理论和实验分析结果表明，此方案可以使服务端选择可靠的用户进行训练，同时能够实现更公平和有效的信誉计算，提高联邦学习的准确性。
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| 关 键 词： | 移动网络 联邦学习 区块链 信誉管理 |
Federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain |
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| Authors: | Ming YANG Xuexian HU Qihui ZHANG Jianghong WEI Wenfen LIU |
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| Affiliation: | 1. Strategic Support Force Information Engineering University, Zhengzhou 450001, China;2. Guilin University of Electronic Technology, Guilin 541004, China |
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| Abstract: | Federated learning is a new distributed machine learning technology, where training tasks are deployed on user side and training model parameters are sent to the server side.In the whole process, participants do not need to share their own data directly, which greatly avoids privacy issues.However, the trust relationship between mobile users in the learning model has not been established in advance, there is hidden safety when users perform cooperative train with each other.In view of the above problems, a federated learning scheme for mobile network based on reputation evaluation mechanism and blockchain was proposed.The scheme allowed the server side to use subjective logic models to evaluate the reputation of participating mobile users and provided them with credible reputation opinions sharing environment and dynamic access strategy interface based on the technique of smart contract of blockchain.Theoretical and experimental analys is results show that the scheme can enable the server side to select reliable users for training.And it can achieve more fair and effective reputation calculations, which improves the accuracy of federated learning. |
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| Keywords: | mobile network federated learning blockchain reputation management |
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