Artificial Identification: A Novel Privacy Framework for Federated Learning Based on Blockchain

CORC > 自动化研究所 > 中国科学院自动化研究所 > 复杂系统管理与控制国家重点实验室 > 先进控制与自动化团队

	Artificial Identification: A Novel Privacy Framework for Federated Learning Based on Blockchain
	Ouyang,Liwei 5,6; Wang,Fei-Yue 4,5; Tian,Yonglin 3; Jia,Xiaofeng 2; Qi,Hongwei 1; Wang,Ge 4
刊名	IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS
	2022-12
页码	1-10
英文摘要	To provide off-chain federations with complete privacy services to realize on-chain federated learning (FL), this article proposes a novel privacy framework for FL based on blockchain and smart contracts, named Artificial Identification. It consists of two modules: private peer-to-peer identification and private FL, using two scalable smart contracts to manage the identification and learning process, respectively. Based on Ethereum and interplenary file systems (IPFS), we implement our framework and comprehensively analyze its performance. Experiments show that the proposed framework has acceptable collaboration costs and offers advantages in terms of privacy, security, and decentralization. Furthermore, combined with radio frequency identification (RFID) technology, the framework has the potential to realize automatic on-chain identification and autonomous FL of machine clusters composed of Internet of Things (IoT) devices or distributed participants.
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/51905]
专题	自动化研究所_复杂系统管理与控制国家重点实验室_先进控制与自动化团队
作者单位	1.the Datang (Beijing) Technology Company, Ltd 2.the Department of Data Management, Beijing Big Data Centre 3.the Department of Automation, University of Science and Technology of China, 4.the Institute of Systems Engineering, Macau University of Science and Technology 5.the State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences 6.the School of Artificial Intelligence, University of Chinese Academy of Sciences
推荐引用方式 GB/T 7714	Ouyang,Liwei,Wang,Fei-Yue,Tian,Yonglin,et al. Artificial Identification: A Novel Privacy Framework for Federated Learning Based on Blockchain[J]. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,2022:1-10.
APA	Ouyang,Liwei,Wang,Fei-Yue,Tian,Yonglin,Jia,Xiaofeng,Qi,Hongwei,&Wang,Ge.(2022).Artificial Identification: A Novel Privacy Framework for Federated Learning Based on Blockchain.IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS,1-10.
MLA	Ouyang,Liwei,et al."Artificial Identification: A Novel Privacy Framework for Federated Learning Based on Blockchain".IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS (2022):1-10.