FederatedCryptix 1.0.0

FederatedCryptix is an innovative and modular framework designed for federated learning with a strong focus on cryptographic security.

FederatedCryptix

Overview

This repository contains a federated learning framework that enables collaborative training of machine learning models across multiple devices while preserving data privacy.

Folder Structure

• config/: Configuration files for models and training parameters.
• encryption/: Contains encryption and decryption logic using TenSEAL.
• models/: Model implementations for TensorFlow and PyTorch.
• communication/: Manages WebSocket communication.
• server/: Central server implementation.
• clients/: Client device implementation.
• utils/: Utility functions and decorators.
• logs/: Log files for server and clients.
• main_server.py: Entry point to start the central server.
• main_client.py: Entry point to start a client device.

Getting Started

Central Server

1. Install dependencies:

   pip install -r requirements.txt