PoC Hybrid Approach

Project structure

• main.py -- script for MNIST experiment (either Linear or CNN model). Defines dataset and dataloaders for trainer
• rnn_main.py -- script for RNN experiment
• trainer.py -- Trainer class that rules training and encryption stuff
• distro.py -- Party and Server classes that knows about model and about encryption and do it
• distro_paillier/ -- sources of Threshold Paillier Homomorphic Encryption. this library is used. I've done minor changes to decrypt function for it to work correctly with float numbers.
• config.py -- containes singleton config object used by all modules.

How to run

1. Install system dependencies for crypto stuff: sudo apt install libgmp-dev libmpfr-dev libmpc-dev.
2. Install python dependencies: pip install -r requirements.txt.
3. Run MNIST experiment python main.py.
4. Run RNN experiment python rnn_main.py.