A survey on federated learning: challenges and applications
Wen, Jie1; Zhang, Zhixia1; Lan, Yang2; Cui, Zhihua2; Cai, Jianghui2; Zhang, Wensheng3
发表期刊INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
ISSN1868-8071
2022-11-11
页码23
通讯作者Cui, Zhihua(cuizhihua@tyustedu.cn)
摘要Federated learning (FL) is a secure distributed machine learning paradigm that addresses the issue of data silos in building a joint model. Its unique distributed training mode and the advantages of security aggregation mechanism are very suitable for various practical applications with strict privacy requirements. However, with the deployment of FL mode into practical application, some bottlenecks appear in the FL training process, which affects the performance and efficiency of the FL model in practical applications. Therefore, more researchers have paid attention to the challenges of FL and sought for various effective research methods to solve these current bottlenecks. And various research achievements of FL have been made to promote the intelligent development of all application areas with privacy restriction. This paper systematically introduces the current researches in FL from five aspects: the basics knowledge of FL, privacy and security protection mechanisms in FL, communication overhead challenges and heterogeneity problems of FL. Furthermore, we make a comprehensive summary of the research in practical applications and prospect the future research directions of FL.
关键词Federated learning Machine learning Privacy protection Personalized federated learning
DOI10.1007/s13042-022-01647-y
关键词[WOS]OBJECTIVE EVOLUTIONARY ALGORITHM ; OPTIMIZATION ALGORITHM ; INTRUSION DETECTION ; ENHANCING SECURITY ; BLOCKCHAIN ; FRAMEWORK ; IMAGE ; MODEL ; RECOMMENDATION ; CLASSIFICATION
收录类别SCI
语种英语
资助项目National Key Research and Development Program of China[2018YFC1604000] ; National Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[61961160707] ; National Natural Science Foundation of China[61976212] ; Science and Technology Development Foundation of the Central Guiding Local[YDZJSX2021A038] ; China University Industry-University-Research Collaborative Innovation Fund (Future Network Innovation Research and Application Project)[2021FNA04014] ; Outstanding Innovation Project for Graduate Students of Taiyuan University of Science and Technology[XCX211004] ; Outstanding Innovation Project for Graduate Students of Taiyuan University of Science and Technology[XCX212081]
项目资助者National Key Research and Development Program of China ; National Natural Science Foundation of China ; Science and Technology Development Foundation of the Central Guiding Local ; China University Industry-University-Research Collaborative Innovation Fund (Future Network Innovation Research and Application Project) ; Outstanding Innovation Project for Graduate Students of Taiyuan University of Science and Technology
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000881886400002
出版者SPRINGER HEIDELBERG
引用统计
被引频次:11[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/50685
专题精密感知与控制研究中心_人工智能与机器学习
通讯作者Cui, Zhihua
作者单位1.Taiyuan Univ Sci & Technol, Sch Elect Informat Engn, Taiyuan, Peoples R China
2.Taiyuan Univ Sci & Technol, Sch Comp Sci & Technol, Taiyuan, Peoples R China
3.Chinese Acad Sci, Inst Automat, State Key Lab Intelligent Control & Management Co, Beijing, Peoples R China
推荐引用方式
GB/T 7714
Wen, Jie,Zhang, Zhixia,Lan, Yang,et al. A survey on federated learning: challenges and applications[J]. INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS,2022:23.
APA Wen, Jie,Zhang, Zhixia,Lan, Yang,Cui, Zhihua,Cai, Jianghui,&Zhang, Wensheng.(2022).A survey on federated learning: challenges and applications.INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS,23.
MLA Wen, Jie,et al."A survey on federated learning: challenges and applications".INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS (2022):23.
条目包含的文件
条目无相关文件。
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Wen, Jie]的文章
[Zhang, Zhixia]的文章
[Lan, Yang]的文章
百度学术
百度学术中相似的文章
[Wen, Jie]的文章
[Zhang, Zhixia]的文章
[Lan, Yang]的文章
必应学术
必应学术中相似的文章
[Wen, Jie]的文章
[Zhang, Zhixia]的文章
[Lan, Yang]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。