https://github.com/bayesianinstitute/flblc

https://github.com/bayesianinstitute/flblc

blockchain federated-learning ipfs smart-contracts

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/bayesianinstitute/flblc
• Owner: bayesianinstitute
• Created: 2023-03-13T01:06:55.000Z (almost 2 years ago)
• Default Branch: main
• Last Pushed: 2023-07-11T13:35:59.000Z (over 1 year ago)
• Last Synced: 2024-08-21T10:13:36.964Z (5 months ago)
• Topics: blockchain, federated-learning, ipfs, smart-contracts
• Language: Python
• Homepage:
• Size: 5.13 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# DiscoFL

Distributed Incentive System for Cooperatively Orchestrated FL

## Authors

- [Faijan Khan](https://github.com/Faizack)

- [Afaan ](https://github.com/afaan123)

## Project overview

### Abstract 

Federated Learning is a novel machine learning paradigm in which a model is trained among distributed participants on local data. Aggregating the individual models with a central server or using decentralized techniques results in a final model that profits from all the local data of the user without having to share it. In this work, we present an architecture for decentralized Federated Learning that uses blockchain to distribute rewards among the participants. We define the notion of trust in such a system and show how our architecture implements trustworthiness. To support our claims, we deliver a prototype application that allows to simulate the full architecture.

For more information, read the full [paper](https://github.com/bayesianinstitute/FLBLC/blob/main/discofl.pdf).

In the `client` folder, you can find the code and the instructions to execute the code.