microsoft / responsible-ai-toolbox-privacyLinks
A library for statistically estimating the privacy of ML pipelines from membership inference attacks
☆35Updated last month
Alternatives and similar repositories for responsible-ai-toolbox-privacy
Users that are interested in responsible-ai-toolbox-privacy are comparing it to the libraries listed below
Sorting:
- Differentially-private transformers using HuggingFace and Opacus☆143Updated last year
- The repository contains the code for analysing the leakage of personally identifiable (PII) information from the output of next word pred…☆101Updated last year
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆74Updated last year
- Membership Inference Competition☆31Updated 2 years ago
- A codebase that makes differentially private training of transformers easy.☆176Updated 2 years ago
- Code for "Differential Privacy Has Disparate Impact on Model Accuracy" NeurIPS'19☆33Updated 4 years ago
- Python library for implementing Responsible AI mitigations.☆67Updated last year
- Private Evolution: Generating DP Synthetic Data without Training [ICLR 2024, ICML 2024 Spotlight]☆102Updated 3 weeks ago
- A toolkit for tools and techniques related to the privacy and compliance of AI models.☆107Updated 3 weeks ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆105Updated last month
- ☆28Updated last year
- Code for Auditing DPSGD☆37Updated 3 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆131Updated 2 months ago
- TextHide: Tackling Data Privacy in Language Understanding Tasks☆31Updated 4 years ago
- This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.☆63Updated 6 years ago
- ☆75Updated 3 years ago
- [ICML 2024 Spotlight] Differentially Private Synthetic Data via Foundation Model APIs 2: Text☆46Updated 9 months ago
- A library for running membership inference attacks against ML models☆150Updated 2 years ago
- [NeurIPS 2021] "G-PATE: Scalable Differentially Private Data Generator via Private Aggregation of Teacher Discriminators" by Yunhui Long*…☆30Updated 3 years ago
- ☆23Updated 2 years ago
- Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models☆127Updated last year
- Code for Findings of ACL 2021 "Differential Privacy for Text Analytics via Natural Text Sanitization"☆29Updated 3 years ago
- Python package to create adversarial agents for membership inference attacks againts machine learning models☆46Updated 6 years ago
- ☆21Updated 4 years ago
- ☆80Updated 3 years ago
- The privML Privacy Evaluator is a tool that assesses ML model's levels of privacy by running different attacks on it.☆18Updated 4 years ago
- [ICLR'24 Spotlight] DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer☆46Updated last year
- autodp: A flexible and easy-to-use package for differential privacy☆276Updated last year
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- ☆148Updated last year