Research code for the concept of transferring adversarial attacks based on dataset intersections.
Demo with CIFAR100:
python run_experiment_ART.py --epoch 25 --attack pgd --adv-steps 50 --num-shared-classes 50 --percent-shared-data 25
This code uses IBM's Adversarial Robustness 360 Toolbox (ART)
@article{art2018,
title = {Adversarial Robustness Toolbox v1.0.0},
author = {Nicolae, Maria-Irina and Sinn, Mathieu and Tran, Minh~Ngoc and Buesser, Beat and Rawat, Ambrish and Wistuba, Martin and Zantedeschi, Valentina and Baracaldo, Nathalie and Chen, Bryant and Ludwig, Heiko and Molloy, Ian and Edwards, Ben},
journal = {CoRR},
volume = {1807.01069},
year = {2018},
url = {https://arxiv.org/pdf/1807.01069}
}
5 commits
Jupyter Notebook
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Python
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Research code for the concept of transferring adversarial attacks based on dataset intersections.
Demo with CIFAR100:
python run_experiment_ART.py --epoch 25 --attack pgd --adv-steps 50 --num-shared-classes 50 --percent-shared-data 25
This code uses IBM's Adversarial Robustness 360 Toolbox (ART)
@article{art2018,
title = {Adversarial Robustness Toolbox v1.0.0},
author = {Nicolae, Maria-Irina and Sinn, Mathieu and Tran, Minh~Ngoc and Buesser, Beat and Rawat, Ambrish and Wistuba, Martin and Zantedeschi, Valentina and Baracaldo, Nathalie and Chen, Bryant and Ludwig, Heiko and Molloy, Ian and Edwards, Ben},
journal = {CoRR},
volume = {1807.01069},
year = {2018},
url = {https://arxiv.org/pdf/1807.01069}
}
5 commits
Jupyter Notebook
88.0%
Python
12.0%