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
- Install dependencies:
pip install -r requirements.txt
1 maintainer
Metadata
1 maintainer
Release files for FederatedCryptix 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| FederatedCryptix-1.0.0.tar.gz | 4.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| FederatedCryptix-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.2 kB
Release files / FederatedCryptix-1.0.0.tar.gz
| Download URL | FederatedCryptix-1.0.0.tar.gz |
|---|---|
| Size | 4.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.8.18
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Release files / FederatedCryptix-1.0.0-py3-none-any.whl
| Download URL | FederatedCryptix-1.0.0-py3-none-any.whl |
|---|---|
| Size | 6.5 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.8.18
|
