Unlearn-Saliency

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

Collection of tools and resources for managing the statistical disclosure control of trained machine learning models

? Model-Driven test data generation platform enabling developers to create realistic, scalable, and privacy-compliant test data. Features model-driven data generation, GDPR compliance, and seamless Python integration.

"Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning" by Chongyu Fan*, Jiancheng Liu*, Licong Lin*, Jinghan Jia, Ruiqi Zhang, Song Mei, Sijia Liu

Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)

Location Privacy Meter: A tool to model human mobility and quantify location privacy

My public and contributable base/wiki/digital garden for cybersecurity, cyber resilience, and cyber-related topics - mixed with some personal. Utilizes Notion, Obsidian, and Github to sync content.

Efficient Secure Aggregation for Privacy-Preserving Federated Machine Learning

Discover the art of enhancing your data using generative modelling in these notebooks.

A modular framework for building and deploying Retrieval-Augmented Generation (RAG) systems with built-in evaluation and monitoring.