github.comrepoTrusted-AI/adversarial-robustness-toolbox
Adversarial Robustness Toolbox (ART) is a Python library, hosted by the Linux Foundation AI & Data Foundation, for evaluating and defending machine learning models against adversarial threats: evasion, poisoning, extraction, and inference attacks. It supports major ML frameworks (TensorFlow, Keras, PyTorch, scikit-learn, XGBoost, LightGBM, CatBoost) across data types (images, tables, audio, video) and tasks (classification, object detection, speech recognition, certification), and was developed with DARPA support.
TL;DR Open-source Python toolkit for testing and defending ML models against evasion, poisoning, extraction, and inference attacks.
Technologies named here
Techniques named here
- Evasion
- Poisoning
- Extraction
- Inference
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