BEAS: Blockchain Enabled Asynchronous & Secure Federated Machine Learning

Overview

BEAS

Blockchain Enabled Asynchronous and Secure Federated Machine Learning

Default Network Configuration:

The default application uses the HyperLedger Test network which bootstraps the following instances:

  1. 1 Orderer
  2. 1 Certifying Authority
  3. 2 org (org0 and org1) maintaining 2 peer (peer0 and peer 1)
  4. 1 CouchDB
  5. 1 CLI

Usage Instructions:

Prerequisites:

  1. HyperLedger Fabric v2.2.x LTS
  2. Download this repository, and merge BEAS/fabric-samples with the HyperLedger fabric-samples directory.

Network Setup:

$  cd fabric-samples/BEAS
$  ./teardownBEAS.sh
$  ./startBEAS.sh

If ./sh files have permission error (mac OS):

$  chmod u+r+x ./file_name.sh

Running the Application:

Initialise New Channel

  1. Change working directory:
$  cd fabric-samples/BEAS/javascript/storageServer
  1. Install Application Dependancies:
$  npm install
  1. Run Application
$  node server.js

Initialise New Client

Initialise New Channel

  1. Change working directory:
$  cd fabric-samples/BEAS/javascript/clientNode
  1. Install Application Dependancies:
$  npm install
  1. Run Application
$  node client.js
  1. To view the frontend, go to your browser and lauch http://localhost:5000
You might also like...
Plato: A New Framework for Federated Learning Research

a new software framework to facilitate scalable federated learning research.

A Research-oriented Federated Learning Library and Benchmark Platform for Graph Neural Networks. Accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks A Research-oriented Federated Learning Library and Benchmark Platform

An unofficial PyTorch implementation of a federated learning algorithm, FedAvg.
An unofficial PyTorch implementation of a federated learning algorithm, FedAvg.

Federated Averaging (FedAvg) in PyTorch An unofficial implementation of FederatedAveraging (or FedAvg) algorithm proposed in the paper Communication-E

Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data
Bachelor's Thesis in Computer Science: Privacy-Preserving Federated Learning Applied to Decentralized Data

federated is the source code for the Bachelor's Thesis Privacy-Preserving Federated Learning Applied to Decentralized Data (Spring 2021, NTNU) Federat

FedScale: Benchmarking Model and System Performance of Federated Learning
FedScale: Benchmarking Model and System Performance of Federated Learning

FedScale: Benchmarking Model and System Performance of Federated Learning (Paper) This repository contains scripts and instructions of building FedSca

Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)

To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/

GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning
GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning

GradAttack is a Python library for easy evaluation of privacy risks in public gradients in Federated Learning, as well as corresponding mitigation strategies.

Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models
Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models

Robbing the FED: Directly Obtaining Private Data in Federated Learning with Modified Models This repo contains a barebones implementation for the atta

Breaching - Breaching privacy in federated learning scenarios for vision and text
Breaching - Breaching privacy in federated learning scenarios for vision and text

Breaching - A Framework for Attacks against Privacy in Federated Learning This P

Comments
Owner
Harpreet Virk
Harpreet Virk
FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning

FEDn is an open-source, modular and ML-framework agnostic framework for Federated Machine Learning (FedML) developed and maintained by Scaleout Systems. FEDn enables highly scalable cross-silo and cross-device use-cases over FEDn networks.

Scaleout 75 Nov 9, 2022
🦕 NanoSaur is a little tracked robot ROS2 enabled, made for an NVIDIA Jetson Nano

?? nanosaur NanoSaur is a little tracked robot ROS2 enabled, made for an NVIDIA Jetson Nano Website: nanosaur.ai Do you need an help? Discord For tech

NanoSaur 162 Dec 9, 2022
MiraiML: asynchronous, autonomous and continuous Machine Learning in Python

MiraiML Mirai: future in japanese. MiraiML is an asynchronous engine for continuous & autonomous machine learning, built for real-time usage. Usage In

Arthur Paulino 25 Jul 27, 2022
FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX.

FedJAX: Federated learning with JAX What is FedJAX? FedJAX is a library for developing custom Federated Learning (FL) algorithms in JAX. FedJAX priori

Google 208 Dec 14, 2022
An open framework for Federated Learning.

Welcome to Intel® Open Federated Learning Federated learning is a distributed machine learning approach that enables organizations to collaborate on m

Intel Corporation 397 Dec 27, 2022
Official code implementation for "Personalized Federated Learning using Hypernetworks"

Personalized Federated Learning using Hypernetworks This is an official implementation of Personalized Federated Learning using Hypernetworks paper. [

Aviv Shamsian 121 Dec 25, 2022
[ICLR'21] FedBN: Federated Learning on Non-IID Features via Local Batch Normalization

FedBN: Federated Learning on Non-IID Features via Local Batch Normalization This is the PyTorch implemention of our paper FedBN: Federated Learning on

Med-AIR@CUHK 156 Dec 15, 2022
[CVPR'21] FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space

FedDG: Federated Domain Generalization on Medical Image Segmentation via Episodic Learning in Continuous Frequency Space by Quande Liu, Cheng Chen, Ji

Quande Liu 178 Jan 6, 2023
Personalized Federated Learning using Pytorch (pFedMe)

Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le

Charlie Dinh 226 Dec 30, 2022