Project Title

PySyft — Secure Data Science on Encrypted Data

Overview

PySyft is an open-source Python library that enables data science on data that remains in someone else's server, without ever seeing or obtaining a copy of the data. It supports any statistical analysis or machine learning, and offers compatibility with third-party Python libraries. PySyft's unique approach to data privacy and security makes it a valuable tool for data scientists working with sensitive or proprietary data.

Key Features

Secure data science on encrypted data
Compatibility with third-party Python libraries
Datasite support for structured transparency
Cross-platform support (Linux, macOS, Windows, Docker, Kubernetes)

Use Cases

Data scientists working with sensitive or proprietary data
Enterprises needing to protect their data while still leveraging it for analysis
Researchers collaborating on projects with privacy concerns

Advantages

Enhances data privacy and security
Allows for data analysis without data transfer
Supports a wide range of statistical and machine learning tasks
Open-source and community-driven

Limitations / Considerations

May require additional setup and configuration for datasites
Performance may be impacted by encryption and data transfer processes
Compatibility with certain third-party libraries may vary

TensorFlow Privacy: A library for training machine learning models with privacy guarantees, but does not focus on data access.
PyCryptoDL: A library for encrypted deep learning, but with a narrower focus on deep learning tasks.
CryptoNets: A framework for privacy-preserving neural networks, but with a focus on neural networks rather than general data science tasks.

Basic Information

GitHub: https://github.com/OpenMined/PySyft
Stars: 9,786
License: Unknown
Last Commit: 2025-09-23

📊 Project Information

Project Name: PySyft
GitHub URL: https://github.com/OpenMined/PySyft
Programming Language: Python
⭐ Stars: 9,786
🍴 Forks: 2,003
📅 Created: 2017-07-18
🔄 Last Updated: 2025-09-23

🏷️ Project Topics

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PySyft

Project Description