ART 1.19.1

This release of ART 1.19.1 provides updates to ART 1.19

Added

[None]

Changed

[None]

Removed

[None]

Fixed

• Fixed string literals in returned AutoAttack metadata to correctly use f-strings (#2550)
• Fixed typing and doctoring on AdversarialPatchPyTorch attack to account for object detection data (#2557)
• Fixed a missing PyTorch transfer to device in ProjectedGradientDescentPyTorch attack (#2558)

ART 1.19.0

This release of ART 1.19.0 introduces Steal Now Attack Later and Rescaling Auto Conjugate Gradient attacks and the Be Your Own Neighbourhood Detector (BEYOND) for adversarial examples.

Added

• Added the Steal Now Attack Later (SNAL) evasion attack (#2440)
• Added the Rescaling Auto Conjugate Gradient (ReACG) descent evasion attack (#2460)
• Added the Be Your Own Neighbourhood Detector (BEYOND) for adversarial examples in PyTorch (#2489)
• Added support for scikit-learn models with multiples outputs (#2505)

Changed

• Changed AutoAttack to allow defining number of processes used in parallel processing (#2529)

Removed

[None]

Fixed

• Fixed use of deprecated function binom_test from scipy (#2517)
• Fixed bug in random sampling of patch locations in masks for adversarial patch attacks in PyTorch (#2539)

ART 1.18.2

This release of ART 1.18.2 provides updates to ART 1.18

Added

[None]

Changed

• Changed version checks for imported libraries requiring checks to use standard library functions (#2500)

Removed

[None]

Fixed

[None]

ART 1.18.1

This release of ART 1.18.1 provides updates to ART 1.18

Added

[None]

Changed

[None]

Removed

[None]

Fixed

• Fixed missing transfer to device/GPU in ProjectedGradientDescentPyTorch (#2455)

ART 1.18.0

This release of ART 1.18.0 introduces Overload Attack on object detection models and provides fast accurate loss gradients in Projected Gradient Descent for all norms.

Added

• Added Overload Attack on object detection models (#2337)
• Added support for all norms in Projected Gradient Descent attacks (#2382)
• Added support for feature scaling in inference attacks (#2384)

Changed

• Replaced model specific estimators for Yolo and Faster-RCNN with single estimator for all object detection models in PyTorch (#2321 )

Removed

[None]

Fixed

• Fixed scaling of gradients of non-L[2, infinity] norms in Projected Gradient Descent attacks (#2382)

ART 1.17.1

This release of ART 1.17.1 provides updates to ART 1.17

Added

[None]

Changed

[None]

Removed

• Removed upper limit for scikit-learn to reduce dependency conflicts and facilitate integration with other libraries.

Fixed

[None]

ART 1.17.0

This release of ART 1.17.0 introduces new adversarial training protocols, membership inference attacks, composite adversarial attacks for evasion and more.

Added

• Added Composite Adversarial Attack as evasion attack in PyTorch (#2287)
• Added support for black-box membership inference attacks without true labels (#2293)
• Added verbose option for progress bars in methods fit and predict of all classification estimators (#2334)
• Added Oracle Aligned Adversarial Training (OAAT) in PyTorch (#2348)

Changed

[None]

Removed

[None]

Fixed

• Fixed bug in ActivateDefense and SpectralSignatures poisoning defences by flattening the outputs when calling get_activations() (#2327)
• Fixed bug in Hugging Face classification estimator to correctly infer device if provided model is already on GPU (#2300)

ART 1.16.0

This release of ART 1.16.0 introduces multiple estimators for certified robustness and Hugging Face models, adversarial training with Adversarial Weight Perturbation, improvements for inference attacks, and more.

Added

• Added estimator for smoothed vision transformers as defence against evasion with adversarial patches (#2171)
• Added estimators for variations of randomised smoothing including MACER, SmoothAdv, and SmoothMix for PyTorch and TensorFlow (#2218)
• Added adversarial training with Adversarial Weight Perturbation protocol in PyTorch (#2224)
• Added estimator for Hugging Face models with PyTorch backend (#2245)
• Added ObjectSeeker certifiably robust defence for object detectors against poisoning and adversarial patches (#2246)
• Added representation string __repr__ to all attacks (#2274)

Changed

• Changed inference attacks to support additional attack model types (e.g., KNN, LR, etc.) and replaced scikit-learn's MLPClassifier with a PyTorch neural network model (#2253)
• Changes attacks's method set_params to raise ValueError if a not previously defined attributed is set (#2257)
• Changed AutoAttack to support multiprocessing and support running attacks in parallel (#2258)

Removed

[None]

Fixed

• Fixed docstring of TargetedUniversalPerturbation (#2212)
• Fixed bug of unsupported operands because of dependency updates in AdversarialPatchTensorFlowV2 (#2276)
• Fixed bug in AutoAttack to avoid that attacks which do not support targeted mode are skipped (#2257)

ART 1.15.2

This release of ART 1.15.2 provides updates to ART 1.15

Added

[None]

Changed

[None]

Removed

[None]

Fixed

• Fixed bug where PyTorchYolo and PyTorchObjectDetector object detection estimators modified the original input Numpy array (#2263)
• Fixed bug where channels_first argument of PyTorchObjectDetector and PyTorchFasterRCNN received the wrong default value of False instead of True (#2264)

ART 1.15.1

This release of ART 1.15.1 provides updates to ART 1.15

Added

[None]

Changed

[None]

Removed

[None]

Fixed

• Fixed deprecation warning by replacing the import statement from scipy.ndimage.filters import median_filter with from scipy.ndimage import median_filter (#2211)
• Fixed bug limiting input shapes in AutoProjectedGradientDescent and AutoConjugateGradient attacks to be images to support any input shapes (#2214)
• Fixed missing support for index-labels in AdversarialTrainerTRADESPyTorch (#2231)
• Fix bug in PyTorchObjectDetector and PyTorchYolo estimators to support non-leaf tensors to retain gradient properties if moved to another device (#2238, #2249)
• Fixed unintended required dependency Pillow to be optional again (#2240)
• Fixed circular dependencies in art.estimators.certification (#2241)