Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization-Reference-Cited by-同舟云学术

Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization

Published:2023-03-01 Issue:2 Volume:20 Page:988-1001
ISSN:1545-5971
Container-title:IEEE Transactions on Dependable and Secure Computing
language:
Short-container-title:IEEE Trans. Dependable and Secure Comput.

Author:

Zheng Yifeng¹^ORCID,Lai Shangqi²^ORCID,Liu Yi³^ORCID,Yuan Xingliang²^ORCID,Yi Xun⁴^ORCID,Wang Cong³^ORCID

Affiliation:

1. School of Computer Science and Technology, Harbin Institute of Technology, Shenzhen, Shenzhen, China

2. Faculty of Information Technology, Monash University, Clayton, VIC, Australia

3. Department of Computer Science, City University of Hong Kong, Hong Kong

4. School of Computing Technologies, RMIT University, Melbourne, VIC, Australia

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Shenzhen High-Level Talents Research Start-up Fund

Australian Research Council

Monash-Data61 collaborative research

Research Grants Council of Hong Kong

Shenzhen Municipality Science and Technology Innovation Commission

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/8858/10068314/09695218.pdf?arnumber=9695218

Reference46 articles.

1. Sealed-Glass Proofs: Using Transparent Enclaves to Prove and Sell Knowledge

2. Fedpaq: A communication-efficient federated learning method with periodic averaging and quantization;reisizadeh;Proc Int Conf Artif Intell Statist,2020

3. Intel software guard extensions,2020

4. Towards federated learning at scale: System design;bonawitz;Proc Conf Mach Learn Syst,2019

5. Fastsecagg: Scalable secure aggregation for privacy-preserving federated learning;kadhe;CoRR,2020

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