Linear-complexity Private Function Evaluation (PFE) based on homomorphic encryption (as presented at ESORICS'20).
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Updated
Sep 14, 2020 - C++
Linear-complexity Private Function Evaluation (PFE) based on homomorphic encryption (as presented at ESORICS'20).
Secure implementations of Edit Distance algorithms using EMP-toolkit garbled circuits
Implementation of protocols in Falcon
Implementation of protocols in SecureNN.
Piranha: A GPU Platform for Secure Computation
SecMML (Queqiao): Secure MPC (multi-party computation) Machine Learning Framework.
MAPLE: Metadata-Hiding Policy-Controllable Encrypted Search Platform
A practical engine for Secure Multiparty Computation (SMPC).
pMPL: A Robust Multi-Party Learning Framework with a Privileged Party. This project is connected with the publication @ ACM CCS 2022.
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
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