@inproceedings{
    ma2021finding,
    title={Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks},
    author={Chen Ma and Xiangyu Guo and Li Chen and Jun-Hai Yong and Yisen Wang},
    booktitle={Thirty-Fifth Conference on Neural Information Processing Systems},
    year={2021},
    url={https://openreview.net/forum?id=g0wang64Zjd}
}

+-- configures
|   |-- HSJA.json  # the hyperparameters setting of HSJA, which is also used in Tangent Attack
+-- dataset
|   |-- dataset_loader_maker.py  # it returns the data loader class that includes 1000 attacks images for the experiments.
|   |-- npz_dataset.py  # it is the dataset class that includes 1000 attacks images for the experiments.
+-- models
|   |-- defensive_model.py # the wrapper of defensive networks (e.g., AT, ComDefend, Feature Scatter), and it converts the input image's pixels to the range of 0 to 1 before feeding.
|   |-- standard_model.py # the wrapper of standard classification networks, and it converts the input image's pixels to the range of 0 to 1 before feeding.
+-- tangent_attack_hemisphere
|   |-- attack.py  # the main class for the attack.
|   |-- tangent_point_analytical_solution.py  # the class for computing the optimal tagent point of the hemisphere.
+-- tangent_attack_semiellipsoid
|   |-- attack.py  # the main class for the attack.
|   |-- tangent_point_analytical_solution.py  # the class for computing the optimal tagent point of the semi-ellipsoid.
+-- cifar_models   # this folder includes the target models of CIFAR-10, i.e., PyramidNet-272, GDAS, WRN-28, and WRN-40 networks.
|-- config.py   # the main configuration of Tangent Attack.
|-- logs  # all the output (logs and result stats files) are located inside this folder
|-- train_pytorch_model  # the pretrained weights of target models
|-- attacked_images  # the 1000 image data for evaluation 

python tangent_attack_hemisphere/attack.py --gpu 0 --norm l2 --dataset CIFAR-10 --arch resnet-50
python tangent_attack_hemisphere/attack.py --gpu 0 --norm l2 --dataset CIFAR-10 --arch gdas
python tangent_attack_semiellipsoid/attack.py --gpu 0 --norm l2 --dataset CIFAR-10 --arch resnet-50
python tangent_attack_semiellipsoid/attack.py --gpu 0 --norm l2 --dataset CIFAR-10 --arch gdas

./tangent_attack_CIFAR_undefended_models.sh