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Implementation Of Secure Multi-Party Computation for a Basic Greater Than Problem

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Secure Multiparty Computation

Welcome to the repository for secure multiparty computation (SMPC) project!

This repository contains a collection of tools and algorithms for performing secure computations in a collaborative environment. SMPC allows multiple parties to jointly compute a function over their private inputs, without revealing anything except the output. This implementation of SMPC solves for a basic "greater than" problem - also know as Yao's Millionaires' Problem. The Yao's Millionaires' Problem, introduced in 1982 by computer scientist Andrew Yao, is a secure multi-party computation issue where two millionaires, Alice and Bob, aim to determine their relative wealth without revealing their actual financial information.

Features

  • Implementations of various SMPC protocols and techniques
  • Support for both additive and arithmetic circuits
  • Optimized for performance and efficiency

Requirements

  • Python 3.x
  • pycryptodome libraries

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Implementation Of Secure Multi-Party Computation for a Basic Greater Than Problem

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