Blockchain Enabled Federated Learning: Approaches, Challenges, and Prospects; [区块链赋能联邦学习:方法尧挑战与展望] - Details

Author：

Sun, E. (Sun, E..) | Dong, X. (Dong, X..) | Zhang, H. (Zhang, H..) | Li, M. (Li, M..) | Zhang, D. (Zhang, D..)

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Scopus

Abstract：

In　response　to　security　and　privacy　in　the　integration　of　blockchain　technology　with　federated　learning　(FL),　comprehensive　review　and　analysis　of　the　relevant　methods　for　empowering　FL　with　blockchain　are　provided.　First,　FL　and　blockchain　were　elucidated　separately,　and　on　the　basis　of　this,　the　state-of-the-art　general　architectures　for　blockchain-enabled　FL　were　summarized.　Second,　the　progress　in　security,　privacy,　incentives,　and　efficiency　methods　was　investigated,　and　the　advantages　and　disadvantages　of　each　method　were　analyzed.　Finally,　the　current　issues　in　blockchain　enabled　FL　were　identified,　and　potential　solutions　were　proposed,　along　with　future　prospects.　©　2025　Beijing　University　of　Technology.　All　rights　reserved.

Keyword：

efficiency data privacy incentive mechanism federated learning (FL) data security blockchain

Author Community：

[ 1 ] [Sun E.]Faulty of Informational Technology, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Sun E.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 3 ] [Dong X.]Faulty of Informational Technology, Beijing University of Technology, Beijing, 100124, China
[ 4 ] [Dong X.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 5 ] [Zhang H.]Faulty of Informational Technology, Beijing University of Technology, Beijing, 100124, China
[ 6 ] [Zhang H.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 7 ] [Li M.]Faulty of Informational Technology, Beijing University of Technology, Beijing, 100124, China
[ 8 ] [Li M.]Beijing Laboratory of Advanced Information Networks, Beijing, 100124, China
[ 9 ] [Zhang D.]Network and Information Technology Center, Beijing University of Technology, Beijing, 100124, China

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Source ：

Journal of Beijing University of Technology

ISSN： 0254-0037

Year： 2025

Issue： 3

Volume： 51

Page： 337-349

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SCOPUS Cited Count：

ESI Highly Cited Papers on the List： 0 Unfold All

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Chinese Cited Count：

30 Days PV： 17

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