三. 一种基于区块链的联邦学习框架(Blockchained On-Device Federated Learning) 据调研,[1] 提出一种基于区块链的联邦学习通用框架(Blockchained On-Device Federated Learning, BlockFL),其具体步骤如下: 1.参数初始化:创建创世块,其包含随机初始化的全局参数等信息。 2.本地模型更新:每一个终端设备从新区块下...
《Blockchain and Federated Learning for Privacy-Preserved Data Sharing in Industrial IoT》笔记 没饭了 想变得有趣的一个顶无趣的人23 人赞同了该文章 该篇论文于2020年6月发布在IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS(CCF-B),通信作者是挪威奥斯陆大学(University of Oslo)的Yan zhang(SeniorMember,IEEE)...
联邦学习论文阅读笔记11 FGFL: A blockchain-based fair incentive governor for Federated Learning 面对的问题:激励分配不均、攻击者欺骗 方法:提出FGFL模型。 1)设计了时间衰减SLM算法度量工作者声誉; 2)设计了基于梯度相似度的轻量级方法度量工作者贡献; 3)提出了一种公平的激励机制FGFL,任务发布者根据声誉与贡...
A Data Sharing Privacy Protection Model Based on Federated Learning and Blockchain Technology As the main driving force for social development in the new era, data sharing is controversial in terms of privacy and security. Traditional privacy protec... F Ren,Z Liang - 《International Journal of ...
Federated learning (FL) is a promising framework for distributed machine learning that trains models without sharing local data while protecting privacy. F
Blockchain technology is an undeniable ledger technology that stores transactions in high-security chains of blocks. Blockchain can solve security and priv
区块链(blockchain) 3.联邦学习分类 记矩阵Di为被数据拥有者i所拥有的数据,每一行代表一个样本(sample),每一列代表一个特征(feature),某些数据集(data sets)可能包含了标签数据(label data)。 记特征空间(feature space)为X,标签空间(label space)为Y,样本ID空间(sample ID space)为I,则特征(feature)X、标签...
applications; in Section 3, we discuss the problem formulation followed by the blockchain and Federated Learning-enabled Secure Architecture for Privacy-Preserving in Smart Healthcare in Section 4; in Section 5, we provide a case study for smart healthcare using Blockchain and Federated Learning. ...
Blockchain and Federated Learning for Privacy-Preserved Data Sharing in Industrial IoTieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8843900 作者:Yunlong Lu Motivation: 1)构建一联邦学习模型,不分享本地数据; 2)提出了一种新的区块链授权协作架构,通过分布式多方共享数据,降低数据泄漏风险,数据所有...
Blockchain-based Federated Learning: A Comprehensive Survey 这篇21年的工作首创地对目前的BCFL (Blockchain-based Federated Learning)做了详细地调查,给上面两个问题提供了一些回答。 为什么要将区块链和联邦学习结合起来? Paper作者认为,传统的联邦学习框架在可靠性上有以下几个问题: ...