Research advances on privacy protection of federated learning

Jianzong WANG; Lingwei KONG; Zhangcheng HUANG; Linjie CHEN; Yi LIU; Chunxi LU; Jing XIAO

doi:10.11959/j.issn.2096-0271.2021030

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Research advances on privacy protection of federated learning

STUDY | 更新时间：2024-06-03

- Research advances on privacy protection of federated learning
- Big data research Vol. 7, Issue 3, Pages: 2021030(2021)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2021030
  CLC： TP311
- Online First：2021-05，
  
  Published：15 May 2021
- 稿件说明：
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Jianzong WANG, Lingwei KONG, Zhangcheng HUANG, et al. Research advances on privacy protection of federated learning[J]. Big data research, 2021, 7(3): 2021030.
DOI：

Jianzong WANG, Lingwei KONG, Zhangcheng HUANG, et al. Research advances on privacy protection of federated learning[J]. Big data research, 2021, 7(3): 2021030. DOI： 10.11959/j.issn.2096-0271.2021030.

摘要

针对隐私保护的法律法规相继出台，数据孤岛现象已成为阻碍大数据和人工智能技术发展的主要瓶颈。联邦学习作为隐私计算的重要技术被广泛关注。从联邦学习的历史发展、概念、架构分类角度，阐述了联邦学习的技术优势，同时分析了联邦学习系统的各种攻击方式及其分类，讨论了不同联邦学习加密算法的差异。总结了联邦学习隐私保护和安全机制领域的研究，并提出了挑战和展望。

Abstract

To this end

many laws and regulations on privacy protection have been introduced

and the phenomenon of data-island has become a major bottleneck hindering the development of big data and artificial intelligence technology.Federated learning has received widespread attention to break this phenomenon.Started with the historical development of federated learning

the definition

and architecture and classification of federated learning

the advantages of federated learning in privacy protection domainwere introduced.At the same time

various attack methods and their classification aboutfederated learning were introduced in detail.The classification of various encryption algorithms in federated learning were summarized.In conclusion

the contribution of federated learning in privacy protection and security mechanism were summarized and the new challenges in these domains were proposed.

关键词

Keywords

references

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Related Institution

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Postdoctoral Research Center, Industrial and Commercial Bank of China

Big Data Development Center of Zhejiang Province

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