Record and Reward Federated Learning Contributions with Blockchain

Martinez, Ismael; Francis, Sreya; Hafid, Abdelhakim Senhaji

doi:10.1109/cyberc.2019.00018

Cited by 92Blockchain Technology Applications and SecurityPrivacy-Preserving Technologies in DataBlockchain Technology in Education and Learning

Record and Reward Federated Learning Contributions with Blockchain

Martinez, Ismael, Francis, Sreya, Hafid, Abdelhakim Senhaji·2019·2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)

DOI 10.1109/cyberc.2019.00018

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Abstract

Although Federated Learning allows for participants to contribute their local data without it being revealed, it faces issues in data security and in accurately paying participants for quality data contributions. In this paper, we propose an EOS Blockchain design and workflow to establish data security, a novel validation error based metric upon which we qualify gradient uploads for payment, and implement a small example of our blockchain Federated Learning model to analyze its performance.

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References 15 · Cited by 92

Authors: Martinez, I., Francis, S., & Hafid, A. S.
Affiliations: Université de Montréal (CA)
ORCID: Martinez, Ismael
Francis, Sreya
Hafid, Abdelhakim Senhaji
Venue: 2019 International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC)
Publisher: IEEE
Published: 2019-10
Pages: 50-57
DOI: 10.1109/cyberc.2019.00018
OpenAlex: W2998460075
Cited by: 92
References: 15
Citations by year: 2026: 4 · 2025: 5 · 2024: 22 · 2023: 23 · 2022: 14 · 2021: 19 · 2020: 5
FWCI: 7.57
Type: conference paper
Language: en
Open access: closed
Licence: ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)
doi.org/10.15223/policy-029 (stm-asf)
doi.org/10.15223/policy-037 (stm-asf)
Locations: International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC) (publishedVersion)
Topics: Physical Sciences › Computer Science › Information Systems › Blockchain Technology Applications and Security
Physical Sciences › Computer Science › Artificial Intelligence › Privacy-Preserving Technologies in Data
Physical Sciences › Computer Science › Information Systems › Blockchain Technology in Education and Learning
Keywords: federated learning, blockchain, data security, reward processing

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