Versatile framework for multi-party computation
-
Updated
Jun 4, 2024 - C++
Versatile framework for multi-party computation
MPyC: Multiparty Computation in Python
An efficient, user-friendly, modular, and extensible framework for mixed-protocol secure multi-party computation with two or more parties
A maliciously secure two-party computation engine which is embeddable and accessible
Extension of the MOTION2NX framework to implement neural network inferencing task where the data is supplied to the “secure compute servers” by the “data providers”.
User-friendly secure computation engine based on secure multi-party computation
The repository is used for presenting the code developed as part of the Adis Hodzic and Casper Knudsens Master Thesis, titled: Stochastic Model Predictive Control of Combined Sewer Overflows in Sanitation Networks
📜 A. Giannopoulos, D. Mouris M.Sc. thesis for University of Athens
open-sourced the SMPCTool.
Fault-tolerant secure multiparty computation in Python.
This the repo for master thesis--SMPC in heavy traffic scenario
Multiparty computation mockup for research purposes
Centralized asynchronous secure aggregation using Shamir's secret sharing for the Boston Women's Workforce Council.
MP-SPDZ implementation of basic graph theory functionality
This repository extends the SCALE-MAMBA repository to support external data providers.
Webpage describing the effort and listing contributed documents and artifacts.
Add a description, image, and links to the smpc topic page so that developers can more easily learn about it.
To associate your repository with the smpc topic, visit your repo's landing page and select "manage topics."