multi-party-computation

Privacy-Preserving Computing Platform 由密码学专家团队打造的开源隐私计算平台，支持多方安全计算、联邦学习、隐私求交、匿踪查询等。

Versatile framework for multi-party computation

Rust implementation of the TLSNotary protocol

MPyC: Multiparty Computation in Python

Implementation of protocols for threshold signatures

A powerful toolkit for building distributed systems and infrastructure as code.

Multi-party computation libraries written in Rust 🦀

JavaScript library for building web-based applications that employ secure multi-party computation (MPC).

A maliciously secure two-party computation engine which is embeddable and accessible

Rust implementation of multi party Ed25519 signature scheme.

Secure Multi-Party Computation (MPC) framework written in Go. Implements two-party garbled circuits (Yao) and the Goldreich-Micali-Wigderson (GMW) protocol for secure computation.

Implementation of protocols in SecureNN.

SecMML (Queqiao): Secure MPC (multi-party computation) Machine Learning Framework.

Piranha: A GPU Platform for Secure Computation

Implementation of protocols in Falcon

Privacy -preserving Neural Networks

Implementation of the FROST protocol for threshold Ed25519 signing

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.

Platform for deploying web-based privacy-preserving data surveys using secure multi-party computation (MPC).