ART 0.1.0

This is the initial release of ART. The following features are currently supported:

• Classifier interface, supporting a few predefined architectures (CNN, ResNet, MLP) for standard datasets (MNIST, CIFAR10), as well as custom models from users
• Attack interface, supporting a few evasion attacks
  • FGM & FSGM
  • Jacobian saliency map attack
  • Carlini & Wagner L_2 attack
  • DeepFool
  • NewtonFool
  • Virtual adversarial method (to be used for virtual adversarial training)
  • Universal perturbation
• Defences
  • Preprocessing interface, currently implemented by feature squeezing, label smoothing, spatial smoothing
  • Adversarial training
• Metrics for measuring robustness: empirical robustness (minimal perturbation), loss sensitivity and CLEVER score
• Utilities for loading datasets, some preprocessing, common maths manipulations
• Scripts for launching some basic pipelines for training, tests and attacking
• Unit tests