This page provides codes for reproducing our results. We use two main libraries here:

• The very awesome SHEEP library prepared by Oliver and Nick to run boolean circuits on ecnrypted data using various homomorphic encryption schemes for our networks.
• Our own general purpose library, matSHEEP, which provides a programmatic interface to design and visualize logic circuits for deep neural networks in python. Find more abour matSHEEP at this link.

There are two main types of experiments.

• Doing Prediction over Encrypted Data using Binary Neural Netwrks.
• Recording accuracies for various levels of sparsity of a binary neural network.

For more information, refer to our paper on arxiv.