Adversarial Robustness Toolbox (ART) is a Python library for Machine Learning Security. ART provides tools that enable developers and researchers to evaluate, defend, certify and verify Machine Learning models and applications against the adversarial threats of Evasion, Poisoning, Extraction, and Inference. ART supports all popular machine learning frameworks (TensorFlow, Keras, PyTorch, MXNet, scikit-learn, XGBoost, LightGBM, CatBoost, GPy, etc.), all data types (images, tables, audio, video, etc.) and machine learning tasks (classification, object detection, generation, certification, etc.).
DEEPSEC is the first implemented uniform evaluating and securing system for deep learning models, which comprehensively and systematically integrates the state-of-the-art adversarial attacks, defenses and relative utility metrics of them.
Foolbox is a Python library that lets you easily run adversarial attacks against machine learning models like deep neural networks. It is built on top of EagerPy and works natively with models in PyTorch, TensorFlow, and JAX.
CleverHans is a Python library of conflicting examples for building attacks, building defenses, and comparing the two.
CleverHans compares the vulnerability of machine learning systems to conflicting examples.
The CleverHans library is under continuous development, always welcoming contributions from the latest attacks and defenses.
Since v4.0.0, CleverHans supports 3 frameworks: JAX, PyTorch and TF2.
CleverHans is currently prioritizing the implementation of attacks in PyTorch however we very much welcome contributions for all 3 frameworks.
The CleverHans library focuses on providing a reference implementation of attacks against machine learning models to facilitate benchmarking of models against conflicting examples.
Adversary attacks are a technique used to trick an artificial intelligence algorithm.
The operation is still essentially an exercise in ethical hacking to strengthen existing algorithms, but other more malicious uses threaten.
Adversary attack algorithms are characterized by a targeted architecture combined with an attack strategy;
Disruption rate, attack success rate and computational costs are also taken into account.
Welcome, my name is Eric Soupet and I am the administrator of the site elodees.com. elodees.com is a state of the art of Artificial Intelligence and aims to be collaborative, you can now offer content such as articles, events, tutorials, ... so don't hesitate !
