Secure multi-party computation: Difference between revisions

Revision as of 12:24, 14 February 2024

Revision as of 12:26, 14 February 2024

Line 217:

* [http://www.brics.dk/SMCL/ Secure Multiparty Computation Language] - project for development of a '___domain specific programming language for secure multiparty computation' and associated cryptographic runtime.

* [https://www.win.tue.nl/~berry/mpyc/ MPyC]: Secure Multiparty Computation in [[Python (programming language)|Python]] (and [[Project Jupyter|Jupyter notebooks]]) — Open-source package for MPC using a customized type of Python coroutines, supporting advanced applications such as ID3 decision trees, linear programming, CNN/MLP neural networks, AES, one-way hash chains, and many more. Launched in May 2018.

* [https://homes.esat.kuleuven.be/~nsmart/SCALE/ SCALE-MAMBA MPC: Secure Computation Algorithms from LEuven] — Framework for various MPC protocols, including the SPDZ family (code available under the [[BSD]]). Offers arithmetic with secret shared values including secure comparison and support for fixed point and floating point arithmetic.

* [https://sharemind.cyber.ee/ Sharemind: analyze confidential data without compromising privacy] — A distributed virtual machine with the capability to run privacy-preserving operations. Has a privacy-preserving programming language for data mining tools. Includes developer tools.

* [https://github.com/mahdiz/mpclib MPCLib: Multi-Party Computation Library] — A library written in C# and C++ that implements several building blocks required for implementing secure multi-party computation protocols. MPCLib has a discrete-event simulation engine that can be used for simulating MPC protocols in virtual networks.