Poster Abstract: OrderlessFL: A CRDT-Enabled Permissioned Blockchain for Federated Learning

Pezhman Nasirifard, Ruben Mayer, Hans Arno Jacobsen

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

1 Scopus citations

Abstract

Industries produce a large amount of data that can improve Machine Learning models. However, due to privacy issues, the data cannot be shared. Several Federated Learning (FL) systems have been introduced as private alternatives without considering Byzantine actors. Also, these systems are affected by the gradient staleness problem. Several blockchain-based FL systems are introduced to address Byzantine actors, which rely on Proof-of-Work-based (PoW) protocols and suffer from their limitations. We introduce OrderlessFL, a safe permissioned blockchain-based FL system using flCRDT, a CRDT for concurrent ML training and mitigating gradient staleness.

Original languageEnglish
Title of host publicationMiddleware 2022 - Proceedings of the 23rd International Middleware Conference Demos and Posters, Part of Middleware 2022
PublisherAssociation for Computing Machinery, Inc
Pages7-8
Number of pages2
ISBN (Electronic)9781450399319
DOIs
StatePublished - 7 Nov 2022
Event23rd International Middleware Conference, Middleware 2022 - Part of Middleware 2022 - Quebec, Canada
Duration: 7 Nov 202211 Nov 2022

Publication series

NameMiddleware 2022 - Proceedings of the 23rd International Middleware Conference Demos and Posters, Part of Middleware 2022

Conference

Conference23rd International Middleware Conference, Middleware 2022 - Part of Middleware 2022
Country/TerritoryCanada
CityQuebec
Period7/11/2211/11/22

Keywords

  • blockchain
  • conflict-free replicated data type
  • federated learning

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