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。
Implementation of protocols for threshold signatures
A framework for building modular AVS and Tangle Blueprints: https://docs.tangle.tools/developers/blueprints/introduction
Rust implementation of the TLSNotary protocol
JavaScript library for building web-based applications that employ secure multi-party computation (MPC).
Multi-party computation libraries written in Rust 🦀
A maliciously secure two-party computation engine which is embeddable and accessible
#区块链#Rust implementation of multi party Ed25519 signature scheme.
Implementation of protocols in SecureNN.
SecMML (Queqiao): Secure MPC (multi-party computation) Machine Learning Framework.
Secure Multi-Party Computation (MPC) with Go. This project implements secure two-party computation with Garbled circuit protocol.
Piranha: A GPU Platform for Secure Computation
Implementation of protocols in Falcon
#计算机科学#Privacy -preserving Neural Networks
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.
Implementation of the FROST protocol for threshold Ed25519 signing
Platform for deploying web-based privacy-preserving data surveys using secure multi-party computation (MPC).
MPC protocols for threshold ECDSA
Turing-Incomplete Programming Language for Multi-Party Computation with Garbled Circuits