Trusted-AI/adversarial-robustness-toolbox 0.3.0

ART 0.3.0

on GitHub

This release brings many new features to ART, including a poisoning module, an adversarial sample detection module and support for MXNet models.

Added

• Access to layers and model activations through the Classifier API
• MXNet support
• Poison detection module, containing the poisoning detection method based on clustering activations
• Jupyter notebook with poisoning attack and detection example on MNIST
• Adversarial samples detection module, containing two detectors: one working based on inputs and one based on activations

Changed

• Optimized JSMA attack (art.attacks.SaliencyMapMethod) - can now run on ImageNet data
• Optimized C&W attack (art.attacks.CarliniL2Method)
• Improved adversarial trainer, now covering a wide range of setups

Removed

• Hard-coded config folder. Config now gets created on the fly when running ART for the first time. Produced config gets stored in home folder ~/.art