A library for Partially Homomorphic Encryption in Python

Security and Privacy Risk Simulator for Machine Learning (arXiv:2312.17667)

SOCI is a Secure Outsourced Computation on Integers based on the Paillier cryptosystem and a twin-server architecture

A pure-Rust implementation of the Paillier encryption scheme

A collection of Paillier cryptosystem zero knowledge proofs

A high-performance homomorphic encryption algorithm library.

A pure-Rust implementation of the Paillier encryption scheme

A Java library for Paillier partially homomorphic encryption.

A Lightweight Partially Homomorphic Encryption Library for Python

Contains Packages for ElGamal, Paillier, Goldweiser-Micali and DGK Homomorphic Encryption System. Also implements secure multiplication, division and comparison.

testing out homomorphic encryption

TNO PET Lab - secure Multi-Party Computation (MPC) - Protocols - Distributed Keygen

Companion repository for blog post on benchmarking implementations of Paillier encryption

Pilatus extends the Talos Framework for Android Applications and/or Smartphone-as-Gateway IoT Applications. Pilatus employs partial homomorphic ciphers (Paillier, EC-ElGamal, proxy-re-encryption PRE, order preserving encryption mOPE, key homomorphic)

Paillier Homomorphic Addition Public Key Cryptosystem

Efficient and Straggler-Resistant Homomorphic Encryption for Heterogeneous Federated Learning

A Julia implementation of the Paillier partially homomorphic encryption system

Extension for the .NET Framework cryptography subsystem, which introduces the Paillier public key cryptosystem with support for homomorphic addition.

Java implementation of Paillier algorithm. This is one of the few known system that preserves additive homomorphic properties. JCA PaillierProvider follows the requirements of Java Cryptography Architecture Reference Guide for Java Platform Standard Edition 6 issued by Oracle.

​ This project implements the partially homomorphic Paillier algorithm and extends and optimizes encryption, decryption, matrix multiplication, and other operations on Numpy matrices, thereby enhancing speed.