[论文笔记]BAFL: A Blockchain-Based Asynchronous Federated Learning Framework melowlz 生活孤独,但不要失去理智和希望贡献 基于区块链技术提出异步联邦学习(AFL)策略,允许每个设备异步地上传本地模型。利用区块链技术防止服务器遭受单点攻击,保证数据的去中心化存储。 为了保证BAFL的效率,作者提出控制出块率的策略以...
“Instead of the traditional federal average (FedAvg) algorithm, this paper evaluates the participating rank and proportion of the local model trained in BAFL of devices. The indices, which consider the training time, training sample size, local update correlation, and global update cheating times,...
Blockchain-based federated learning methodologies in smart environments.BlockchainFederated learningPrivacySecurityInternet of Things (IoT)Blockchain technology is an undeniable ledger technology that stores transactions in high-security chains of blocks. Blockchain can solve security and privacy issues in a...
Our approach begins by utilizing deep learning to anonymize sensitive healthcare data, ensuring the protection of individual identities. Subsequently, this anonymized data is securely stored on IPFS, A decentralized and tamperproof data storage platform. We employ federated learning to improve models ...
This article presents the Blockchain-enabled Federated Learning model for secured communication in the healthcare Internet of Things (BFL-hIoT), with the intention of ensuring the safety and confidentiality of healthcare data that is used in the training of deep learning models. The BFL-hIoT mod...
As an emerging distributed machine learning (ML) technology, federated learning can protect data privacy through collaborative learning AI models across a large number of IoT devices. However, inefficiency and vulnerability to poisoning attacks have slowed federated learning performance. To solve the above...
This study presents the implementation of a blockchain-based federated-learning (FL) intrusion detection system. This approach utilizes machine learning (ML) instead of traditional signature-based methods, enabling the system to detect new attack types. The FL technique ensures the privacy of sensitive...
本文提出的框架名字叫BFLC(Blockchain-based Federated Learning framework with Committee consensus ) BFLC 传统的中心化的联邦学习框架是由中心服务器向向客户端节点下发当前的全局模型,客户端节点收到后进行本地模型训练,完成后,向服务器上传模型更新,服务器聚合形成新的全局模型。迭代上述过程,直到全局模型精度或通...
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: ...
Process#Data Support#Incentive Support#Regulatory and Audit Support#Blockchain-Based Federated Learning Incentive Algorithms#Model Quality Assessment Incentive Algorithm#Weighted Incentive Algorithm#Incentive Allocation Algorithm#Implementation of a Blockchain-Based Federated Learning System#System Model#System ...