典型文献
Safeguarding cross-silo federated learning with local differential privacy
文献摘要：
Federated Learning(FL)is a new computing paradigm in privacy-preserving Machine Learning(ML),where the ML model is trained in a decentralized manner by the clients,preventing the server from directly accessing privacy-sensitive data from the clients.Unfortunately,recent advances have shown potential risks for user-level privacy breaches under the cross-silo FL framework.In this paper,we propose addressing the issue by using a three-plane framework to secure the cross-silo FL,taking advantage of the Local Differential Privacy(LDP)mechanism.The key insight here is that LDP can provide strong data privacy protection while still retaining user data statistics to preserve its high utility.Experimental results on three real-world datasets demonstrate the effectiveness of our framework.
文献关键词：
中图分类号：
作者姓名：
Chen Wang;Xinkui Wu;Gaoyang Liu;Tianping Deng;Kai Peng;Shaohua Wan
作者机构：
School of Electronic Information and Communications,Huazhong University of Science and Technology,Wuhan,430 074,China;Hubei Key Laboratory of Smart Internet Technology,Huazhong University of Science and Technology,Wuhan,430 074,China;Shenzhen Institute for Advanced Study,University of Electronic Science and Technology of China,Shenzhen 518110,China
文献出处：
引用格式：
[1]Chen Wang;Xinkui Wu;Gaoyang Liu;Tianping Deng;Kai Peng;Shaohua Wan-.Safeguarding cross-silo federated learning with local differential privacy)[J].数字通信与网络（英文）,2022(04):446-454
A类：
Safeguarding
B类：
cross,silo,federated,learning,local,differential,privacy,Federated,Learning,FL,new,computing,paradigm,preserving,Machine,ML,where,model,trained,decentralized,manner,by,clients,preventing,server,from,directly,accessing,sensitive,Unfortunately,recent,advances,have,shown,potential,risks,user,level,breaches,under,framework,In,this,paper,we,propose,addressing,issue,using,three,plane,secure,taking,advantage,Local,Differential,Privacy,LDP,mechanism,key,insight,that,can,provide,strong,protection,while,still,retaining,statistics,preserve,its,high,utility,Experimental,results,real,world,datasets,demonstrate,effectiveness,our
AB值：
0.679262
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