Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Interpretability and explainability of data and machine learning models

Uncertainty Quantification 360 (UQ360) is an extensible open-source toolkit that can help you estimate, communicate and use uncertainty in machine learning model predictions.

Paddle with Decentralized Trust based on Xuperchain

Athena: A Framework for Defending Machine Learning Systems Against Adversarial Attacks

Hands on workshop material evaluating performance, fairness and robustness of models