Countly is a product analytics platform that helps teams track, analyze and act-on their user actions and behaviour on mobile, web and desktop applications.

An open-source framework for detecting, redacting, masking, and anonymizing sensitive data (PII) across text, images, and structured data. Supports NLP, pattern matching, and customizable pipelines.

Diffprivlib: The IBM Differential Privacy Library

Awesome Machine Unlearning (A Survey of Machine Unlearning)

OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.

All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.

Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.

The Privacy Engineering & Compliance Framework

Privacy details of SDKs for Apple Privacy Nutrition & Google Safety Section disclosure.

An easy-to-use federated learning platform

A permissionless blockchain network to manage digital identity and access rights

Data security framework for Clojure

[ICLR24 (Spotlight)] "SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation" by Chongyu Fan*, Jiancheng Liu*, Yihua Zhang, Eric Wong, Dennis Wei, Sijia Liu

A curated list of data privacy and security resources

A curated list of Federated Learning papers/articles and recent advancements.

Statify – statistics plugin for WordPress

Python package for simple implementations of state-of-the-art LDP frequency estimation algorithms. Contains code for our VLDB 2021 Paper.

A workshop on data privacy methods for data scientists.

[NeurIPS23 (Spotlight)] "Model Sparsity Can Simplify Machine Unlearning" by Jinghan Jia*, Jiancheng Liu*, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, Sijia Liu

[ACL 2024] Code and data for "Machine Unlearning of Pre-trained Large Language Models"