Versatile framework for multi-party computation
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Updated
May 27, 2024 - C++
Versatile framework for multi-party computation
Rust implementation of the TLSNotary protocol
MPyC: Multiparty Computation in Python
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。
Secure Multi-Party Computation (MPC) with Go. This project implements secure two-party computation with Garbled circuit protocol.
Multi-party computation libraries written in Rust 🦀
A framework for building modular AVS and Tangle Blueprints: https://docs.tangle.tools/developers/blueprints.
A hub for real-world MPC deployments
Turing-Incomplete Programming Language for Multi-Party Computation with Garbled Circuits
pMPL: A Robust Multi-Party Learning Framework with a Privileged Party. This project is connected with the publication @ ACM CCS 2022.
Fault-tolerant secure multiparty computation in Python.
A practical engine for Secure Multiparty Computation (SMPC).
JavaScript library for building web-based applications that employ secure multi-party computation (MPC).
Rust implementation of multi party Ed25519 signature scheme.
Docker CLI package for the vantage6 infrastructure
A POC Python implementation of the Millionaires' problem using Yao's Garbled Circuit protocol.
A maliciously secure two-party computation engine which is embeddable and accessible
Semaphore Merkle Tree Batcher MPC Trusted Setup Ceremony tool
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.
This is a recommended paper list for the course of Privacy Computing.
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