ml-mpc

ML-MPC: Privacy-Preserving Machine Learning

A privacy-preserving machine learning system using Multi-Party Computation (MPC) on the Partisia Blockchain. This project demonstrates how to build a secure ML system where model parameters and user data remain private during inference.

Project Structure

ml-mpc/
├── frontend/          # Next.js frontend application
├── backend/          # Python ML training and model conversion
├── contracts/        # Rust smart contracts for MPC
└── docs/            # Additional documentation

Components

Frontend (Next.js)

• User interface for model interaction
• Secure data input handling
• Real-time result visualization
• Integration with smart contracts

Backend (Python)

• Model training pipeline
• Data preprocessing
• Model conversion to MPC format
• Parameter encryption

Smart Contracts (Rust)

• MPC protocol implementation
• Secure parameter storage
• Privacy-preserving inference
• Result verification

Getting Started

1. Set up the frontend:

   cd frontend
   npm install
   npm run dev

2. Configure the backend:

   cd backend
   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate
   pip install -r requirements.txt

3. Build the smart contracts:

   cd contracts
   cargo build

Development Workflow

1. Train and prepare the model using the Python backend
2. Deploy the model parameters to the blockchain
3. Build and deploy the smart contracts
4. Start the frontend application
5. Test the complete system

Security Features

• Privacy-preserving model inference
• Encrypted parameter storage
• Secure data transmission
• Zero-knowledge proofs
• Multi-party computation

Prerequisites

• Node.js 18+
• Python 3.8+
• Rust (latest stable)
• Partisia Blockchain CLI
• Docker (optional)

Environment Setup

1. Create .env files in each component:

   # frontend/.env
   NEXT_PUBLIC_CONTRACT_ADDRESS=your_contract_address
   NEXT_PUBLIC_NODE_URL=your_node_url
   
   # backend/.env
   MODEL_PATH=path_to_model
   TRAINING_DATA_PATH=path_to_data
   
   # contracts/.env
   PRIVATE_KEY=your_private_key
   NODE_URL=your_node_url

Testing

1. Frontend tests:

   cd frontend
   npm run test

2. Backend tests:

   cd backend
   python -m pytest

3. Contract tests:

   cd contracts
   cargo test

Deployment

1. Deploy smart contracts:

   cd contracts
   cargo run --release

2. Deploy frontend:

   cd frontend
   npm run build
   npm run start

Contributing

Please refer to the main repository README for contribution guidelines.

License

This project is licensed under the MIT License - see the LICENSE file for details.