Privacy-preserving aggregation in federated learning: a survey

Privacy-preserving aggregation in federated learning: a survey

Over the recent years, with the increasing adoption of Federated Learning (FL) algorithms and growing concerns over personal data privacy, Privacy-Preserving Federated Learning (PPFL) has attracted tremendous attention from both academia and industry. Practical PPFL typically allows multiple partici...

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Bibliographic Details
Main Authors: Liu, Ziyao, Guo, Jiale, Yang, Wenzhuo, Fan, Jiani, Lam, Kwok-Yan, Zhao, Jun
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2023
Subjects:
Engineering::Computer science and engineering
Computational Modeling
Cryptography
Online Access:https://hdl.handle.net/10356/164430

Internet

https://hdl.handle.net/10356/164430

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