Pinned Repositories
adversarial-robustness-toolbox
Python library for adversarial machine learning (evasion, extraction, poisoning, verification, certification) with attacks and defences for neural networks, logistic regression, decision trees, SVM, gradient boosted trees, Gaussian processes and more with multiple framework support
PrivacyFrmwkResources
This repository contains resources to support organizations’ use of the Privacy Framework. Resources include crosswalks, Profiles, guidance, and tools. NIST encourages new contributions and feedback on these resources as part of the ongoing collaborative effort to improve implementation of the Privacy Framework.
ai-minimization-toolkit
A toolkit for reducing the amount of personal data needed to perform predictions with a machine learning model
ai-privacy-toolkit
A toolkit for tools and techniques related to the privacy and compliance of AI models.
adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams
PrivacyFrmwkResources
This repository contains resources to support organizations’ use of the Privacy Framework. Resources include crosswalks, Profiles, guidelines, and tools. NIST encourages new contributions and feedback on these resources as part of the ongoing collaborative effort to improve implementation of the Privacy Framework.
abigailgold's Repositories
abigailgold/adversarial-robustness-toolbox
Python library for adversarial machine learning (evasion, extraction, poisoning, verification, certification) with attacks and defences for neural networks, logistic regression, decision trees, SVM, gradient boosted trees, Gaussian processes and more with multiple framework support
abigailgold/PrivacyFrmwkResources
This repository contains resources to support organizations’ use of the Privacy Framework. Resources include crosswalks, Profiles, guidance, and tools. NIST encourages new contributions and feedback on these resources as part of the ongoing collaborative effort to improve implementation of the Privacy Framework.