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ART 1.5.2

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@beat-buesser beat-buesser released this 20 Feb 01:11
· 5099 commits to main since this release

This release of ART 1.5.2 provides updates to ART 1.5.

Added

  • Added new method reset_patch to art.attacks.evasion.adversarial_patch.* to reset patch (#863)
  • Added passing kwargs to internal attacks of art.attacks.evasion.AutoAttack (#850)
  • Added art.estimators.classification.BlackBoxClassifierNeuralNetwork as black-box classifier for neural network models (#849)
  • Added support for channels_first=False for art.attacks.evasion.ShadowAttack in PyTorch (#848)

Changed

  • Changed Numpy requirements to be less strict to resolve conflicts in dependencies (#879)
  • Changed estimator requirements for art.attacks.evasion.SquareAttack and art.attacks.evasion.SimBA to include NeuralNetworkMixin requiring neural network models (#849)

Removed

[None]

Fixed

  • Fixed BaseEstimator.set_params to set preprocessing and preprocessing_defences correctly by accounting for art.preprocessing.standardisation_mean_std (#901)
  • Fixed support for CUDA in art.attacks.inference.membership_inference.MembershipInferenceBlackBox.infer (#899)
  • Fixed return in art.preprocessing.standardisation_mean_std.StandardisationMeanStdPyTorch to maintain correct dtype (#890)
  • Fixed type conversion in art.evaluations.security_curve.SecurityCurve to be explicit (#886)
  • Fixed dtype in art.attacks.evasion.SquareAttack for norm=2 to maintain correct type (#877)
  • Fixed missing CarliniWagnerASR in art.attacks.evasion namespace (#873)
  • Fixed support for CUDA i `art.estimators.classification.PyTorchClassifier.loss (#862)
  • Fixed bug in art.attacks.evasion.AutoProjectedGradientDescent for targeted attack to correctly detect successful iteration steps and added robust stopping criteria if loss becomes zero (#860)
  • Fixed bug in initialisation of search space in art.attacks.evasion.SaliencyMapMethod (#843)
  • Fixed bug in support for video data in art.attacks.evasion.adversarial_patch.AdversarialPatchNumpy (#838)
  • Fixed bug in logged success rate of art.attacks.evasion.ProjectedGradientDescentPyTorch and art.attacks.evasion.ProjectedGradientDescentTensorFlowV2 to use correct labels (#833)