All code (.ipynb files) related to attack experiments is in the attacks/ folder.
Our FGSM and MI-FGSM implementations are in the [summarize/attack.py]
Caveat:
We use Google Colab Pro to run the code. Some blocks are related to loading the gdrive folder.
There are some blocks related to the checkpoints of our pre-trained classifiers. If you are interested in getting these checkpoint data, please contact us.
Random Initialization
SAP
renet18.py is the file for building network without SAP moudle.
renet18SAP.py is the file for building network with SAP moudle.
SAP-like-networks.ipynb is the file for generating multiple SAP-like networks.
Super-Resolution-Based Defense
clean_images is the folder to store the original clean images.
perturbed_images is the folder to store the adversarial attack images.
denoised_images is the folder to store the wavelet denoised images.
recoverd_images is the folder to store the super resolved images.
attack.py is the file to generate attack samples.
cifarresnet.py is the file for defense classification.
components.py is the file for network components.
edsr.py is the file for image super resolution using EDSR.
denoising.py is the file for image wavelet denoising.
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