Real, working examples for Fully Homomorphic Encryption development.
ML Examples (ml/)
Production-ready machine learning on encrypted data:
| Example | Description | Data |
|---|---|---|
| credit_scoring/ | Credit risk prediction | HMEQ dataset |
| disease_prediction/ | Healthcare predictions | Medical records |
| cifar/ | Image classification | CIFAR-10 |
| federated_learning/ | Distributed training | - |
| hybrid_model/ | Mixed FHE/plaintext | - |
Quick Start
cd ml/credit_scoring python -m venv .venv && source .venv/bin/activate pip install -r requirements.txt jupyter lab CreditScoring.ipynb
Deployment Examples (deployment/)
Production deployment patterns:
| Example | Description |
|---|---|
| breast_cancer/ | Cancer detection API |
| sentiment_analysis/ | NLP on encrypted text |
| server/ | FHE inference server |
Blockchain Examples (blockchain/)
FHE for smart contracts:
| Example | Description |
|---|---|
| hardhat-template/ | Solidity + FHE |
| react-template/ | React dApp + FHE |
Requirements
- Python 3.10+
- For ML:
pip install torus-ml - For blockchain: Node.js 18+
Related
- luxfhe/docs - Documentation
- luxfhe/handbook - Deep dive
- luxfhe/workshop - Tutorials
License
Apache 2.0