Skip to content

Latest commit

 

History

History
26 lines (18 loc) · 805 Bytes

README.md

File metadata and controls

26 lines (18 loc) · 805 Bytes

HE_MIA: Homomorphic Encryption for Membership Inference Attacks

Build Python Wheelhouse

The repository contains a list of resources to use a homomorphically encrypted inference from any logistic regression whose weights size is smaller than 214 floating point elements.

From the wheelhouse directory, take the version according to your version of Python. Currently it only works in Linux environments.

Installation

git clone <repo_address>
cd wheelhouse
pip3 install <installer>.whl

Basic usage

from HELR import HELR
...
my_private_inferece = HELR(weights, bias)
result = my_private_inference.predict(sample)
...