FLCert: Provably Secure Federated Learning Against Poisoning Attacks-Reference-Cited by-同舟云学术

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FLCert: Provably Secure Federated Learning Against Poisoning Attacks

Published:2022 Issue: Volume:17 Page:3691-3705
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Cao Xiaoyu¹^ORCID,Zhang Zaixi²^ORCID,Jia Jinyuan³^ORCID,Gong Neil Zhenqiang⁴^ORCID

Affiliation:

1. Meta Platforms, Menlo Park, CA, USA

2. School of Computer Science and Technology, University of Science and Technology of China, Hefei, China

3. Department of Computer Science, University of Illinois Urbana–Champaign, Urbana, IL, USA

4. Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA

Funder

National Science Foundation

Army Research Office

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

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

Link

https://ieeexplore.ieee.org/ielam/10206/9652463/9911773-aam.pdf

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4. Enhancing Robustness within the Collaborative Federated Learning Framework: A Novel Grouping Algorithm for Edge Clients;Applied Sciences;2024-04-12

5. FlexibleFL: Mitigating poisoning attacks with contributions in cloud-edge federated learning systems;Information Sciences;2024-04

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