ARMORY v0.11.1

Changelog

Breaking Changes

• Configs using cifar/mnist datasets require updated docker container
• Custom scenarios require additional parameters

Datasets

• Enhanced Pytorch data loaders (#707)
• TFDS version upgrade (#722). NOTE: requires use of 0.11.1 or newer Docker container for CIFAR/MNIST datasets

Scenarios

• Updated poisoning scenario for Eval 1 Round 1 (#660)
• Enable use_label in audio and video scenarios (#686)
• Set classifier inputs to be immutable (#725)

Attacks

• Allow targeted attacks with systematic label selection such as a round-robin scheme or random targets (#690)
• Wrapper for ART patch attacks to enable better integration with Armory (#694)

Adversarial Datasets

• Label adversarial examples for RESISC45 dataset (#655)

Evaluation Infrastructure

• Custom pathing for evaluations (#663)
• Add flag for number of evaluation batches (#668)
• Disable shuffling of data during evaluation (#675)
• Create perturbation-accuracy plots from .json outputs (#689)
• Option to skip benign classification (#713)
• Add a --no-gpu flag (#733)

Metrics

• Computational resource usage metrics (#703)
• Image patch area metric (#701)
• Video metrics (#717)
• Allow multiple perturbation metrics (#735)

Documentation

• Update command line argument documentation (#681)
• Add dataset licensing details (#685)

User interface

• Allow armory configure to modify existing configuration (#736)