Multi-Party Computation API
A platform for deploying web-based privacy-preserving data surveys using secure multi-party computation.
Overview
WEB-MPC is an open-source platform designed to facilitate privacy-preserving data collection and aggregation through secure multi-party computation (MPC) techniques. It enables multiple participants to submit sensitive data via web interfaces without exposing individual inputs to others, ensuring confidentiality throughout the data collection process. The platform is particularly suited for scenarios where privacy is critical, such as surveys, research studies, or any collaborative data analysis requiring strong data protection guarantees.
The core of WEB-MPC relies on the JIFF MPC library, bundled as a submodule, and requires a Node.js environment, MongoDB for data storage, and Docker for containerized deployment. It supports multiple deployments, allowing different data collection campaigns to run with distinct configurations, data templates, and HTTPS settings. Users interact with the system through a web UI to generate sessions, manage participation links, collect data, and unmask aggregated results securely.
What sets WEB-MPC apart is its web-native approach to MPC, making privacy-preserving computations accessible without specialized client software. Its modular deployment system and integration with standard web technologies simplify setup and customization. The platform includes end-to-end testing suites to verify deployments and supports secure production deployment practices, including reverse proxy setups with Nginx and Let's Encrypt. Developers can get started by cloning the repository, installing dependencies, and running the Docker-compose setup or following detailed AWS EC2 deployment instructions provided in the documentation.
The Problem
Collecting sensitive data from multiple participants often risks exposing individual inputs to other parties or centralized servers. Traditional data aggregation methods lack strong privacy guarantees, making it difficult to conduct confidential surveys or analyses without compromising participant privacy.
The Solution
Key Features
Session Management
Generate and manage secure sessions with keys and passwords to control data collection and unmasking.
Participant Link Generation
Create unique participation links for contributors to submit data securely.
Data Template Configuration
Define input data structures via JSON templates that also render the web UI forms.
Key Strengths
How Developers Use Multi-Party Computation API
Privacy-Preserving Research Surveys
Researchers can collect sensitive participant data without exposing individual responses, ensuring confidentiality in studies.
Secure Collaborative Data Analysis
Organizations can aggregate private inputs from multiple parties to compute joint statistics without revealing raw data.
Enterprise Data Collection Campaigns
Businesses can deploy multiple data collection campaigns with customizable templates and secure session management.
Works Well With
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Ethereum
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Pricing
Open Source | |
|---|---|
| Price (Monthly) | Free |
| Price (Annual) | Free |
| Messaging | N/A |
| Support | Community support via GitHub |
| Analytics |
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Resources
WEB-MPC provides comprehensive documentation, including setup instructions for local and AWS EC2 deployments, usage guides for session and participant management, and testing procedures. The repository includes links to the JIFF MPC library and licensing details.