Secure Multiparty Computation Python Packages

mpyc

MPyC: Multiparty Computation in Python

nilql

Python library for working with encrypted data within nilDB queries and replies.

secretflow

A unified framework for privacy-preserving data analysis and machine learning

shamirs

Minimal pure-Python implementation of Shamir's secret sharing scheme.

spu

SPU (Secure Processing Unit) aims to be a provable, measurable secure computation device, which provides computation ability while keeping your private data protected.

secretflow-serving-lib

SecretFlow-Serving is a serving system for privacy-preserving machine learning models.

secretflow-lite

SecretFlow Lite

oblivious

Python library that serves as an API for common cryptographic primitives used to implement OPRF, OT, and PSI protocols.

sf-sml

Secretflow Secure Machine Learning

cicada-mpc

Fault-tolerant secure multiparty computation in Python.

additive

Data structure for representing additive secret shares of integers, designed for use within secure MPC protocol implementations.

blindfold

Python library for working with encrypted data within nilDB queries and replies.

mpyc-custom

MPyC: Multiparty Computation in Python

exclusive

Data structure for representing secret shares of byte vectors based on bitwise XOR, designed for use within secure multi-party computation (MPC) protocol implementations.

fedscgen

A lightweight, pip-installable version of FedscGen.

otc

Oblivious transfer (OT) communications protocol message/response functionality implementations based on Curve25519 and the Ristretto group.

tinynmc

Minimal pure-Python implementation of a secure multi-party computation (MPC) protocol for evaluating arithmetic sum-of-products expressions via a non-interactive computation phase.

latticex-rosetta

A Privacy-Preserving Framework Based on TensorFlow

latticex

A Privacy-Preserving Framework Based on TensorFlow