Blockchain-Based Decentralized Federated Learning

Ahmed Dirir, Khaled Salah, Davor Svetinovic, Raja Jayaraman, Ibrar Yaqoob, Salil S. Kanhere

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

Federated learning (FL) has gained great traction in recent years. It can provide a privacy-preserving mechanism to train machine learning models on hidden data. However, most of today's FL systems use a centralized server to build the global FL model. Such centralization raises trust and fairness issues stemming from the fact that the FL server may have the ability to reconstruct the original data successfully. In this paper, we propose a blockchain-based decentralized FL system. The FL process in the proposed system is composed of two stages. In the first stage, FL nodes reach a consensus on the training configurations using smart contracts. In the second stage, nodes aggregate the model updates using a novel decentralized aggregation method. The proposed system efficiently schedules aggregation tasks between decentralized nodes, handles dropouts, and detects malicious acts. We test and analyze our solution using Ethereum smart contracts and Python. The implementation and testing details of the algorithms are presented, and all codes are publicly available on GitHub.

Original languageBritish English
Title of host publication2022 4th International Conference on Blockchain Computing and Applications, BCCA 2022
EditorsMohammad Alsmirat, Moayad Aloqaily, Yaser Jararweh, Izzat Alsmadi
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages99-106
Number of pages8
ISBN (Electronic)9781665499583
DOIs
StatePublished - 2022
Event4th International Conference on Blockchain Computing and Applications, BCCA 2022 - San Antonio, United States
Duration: 5 Sep 20227 Sep 2022

Publication series

Name2022 4th International Conference on Blockchain Computing and Applications, BCCA 2022

Conference

Conference4th International Conference on Blockchain Computing and Applications, BCCA 2022
Country/TerritoryUnited States
CitySan Antonio
Period5/09/227/09/22

Keywords

  • AI
  • Blockchain
  • Decentralized Federated Learning
  • Deep Learning
  • Trust

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