Privacy-Preserving Federated Learning With Malicious Clients and Honest-but-Curious Servers-Reference-Cited by-同舟云学术

Privacy-Preserving Federated Learning With Malicious Clients and Honest-but-Curious Servers

Published:2023 Issue: Volume:18 Page:4329-4344
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Le Junqing¹,Zhang Di¹^ORCID,Lei Xinyu²^ORCID,Jiao Long³^ORCID,Zeng Kai³^ORCID,Liao Xiaofeng¹^ORCID

Affiliation:

1. Key Laboratory of Dependable Service Computing in Cyber Physical Society, Ministry of Education, and the College of Computer Science, Chongqing University, Chongqing, China

2. Department of Computer Science, Michigan Technological University, Houghton, MI, USA

3. Department of Electrical and Computer Engineering, George Mason University, Fairfax, VA, USA

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

China Postdoctoral Science Foundation

Natural Science Foundation of Chongqing, China

Natural Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/9970396/10184496.pdf?arnumber=10184496

Reference48 articles.

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4. Privacy-preserving deep learning;shokri;Proc ACM SIGSAC Conf Comput Commun Secur (CCS),2015

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