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Awesome PETs Awesome

A curated list of resources for privacy-enhancing technologies

Contents

General

General resources about PETs and related concepts

For general privacy tools and services, see the Awesome Privacy List (github: pluja/awesome-privacy).

Articles

Books

  • Practical Data Privacy - An overview of privacy and how to apply it in technical systems and organizations. Includes introductions to various PETs.

  • Real World Cryptography - The majority of the book is an introduction to cryptography and cryptographic applications with additional material covering PETs such as multi-party computation, homomorphic encryption, zero-knowledge proofs, and cryptographic hardware.

Blogs

  • OpenMined Blog - Blog of the open-source group OpenMined with several posts on PETs and privacy tech.

Papers

Podcasts

  • Shifting Privacy Left - Podcast hosted by privacy and legal expert Debra J Farber featuring interviews and discussions with various privacy and PETs experts.

Differential Privacy

See the Awesome Differential Privacy List (github: menisadi/awesome-differential-privacy).

Organizations

  • DifferentialPrivacy.org - A website with resources curated by the DP research community. It includes several courses, videos, surveys, and links to other resources.

  • OpenDP - Open-source group developing DP tools.

Blogs

Books

Open-Source Tools

  • OpenDP - Python bindings for OpenDP's Rust-based framework.

Papers

Videos

Privacy-Preserving Federated Learning

Note: Federated learning by itself does not guarantee data privacy, but when used in combination with other PETs it can become privacy-preserving.

There are several different Awesome lists for federated learning, but this one seems to be the most popular. Note that it's federated learning generally, not just PPFL: https://github.com/innovation-cat/Awesome-Federated-Machine-Learning

Papers

Open-Source Tools

  • APPFL - Advanced Privacy-Preserving Federated Learning built my Argonne National Labs aimed at high-performance computing applications. Includes differential-privacy and the ability to incorporate other PETs

  • FedML - Github Repository: https://github.com/fedml-ai/fedml

  • Flower - A unified FL framework available in multiple languages. Flower does not include privacy preservation itself, but is intended to be used in conjunction with other ML and PPML frameworks.

  • OpenFL - Open-source FL framework hosted by the Linux Foundation.

Homomorphic Encryption

See the Awesome Homomorphic Encryption List (github: jonaschn/awesome-he).

Organizations

Blogs

Secure Multiparty Computation

See the Awesome MPC List (github: rdragos/awesome-mpc).

Organizations

  • MPC Alliance - Industry group devoted to increasing adoption of MPC. Includes links to several books and videos.

Videos

Synthetic Data

Tools

DataSynthesizer - A Python-based tool for generating differentally-private synthetic data

Zero-knowledge Proofs and zk-SNARKs

See the Awesome Zero Knowledge Proofs List (github: https://github.com/matter-labs/awesome-zero-knowledge-proofs)

Organizations

  • ZKProof - An open-industry academic initiative seeking to develop standards for ZKPs. The organization also conducts workshops, publishes research, educational material, etc.

Blogs and Tutorials

Papers

Videos

Privacy-preserving Hardware

Blogs

Contribute

Contributions welcome! Read the contribution guidelines first.

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