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This is the repo for exploring data augmentation for adversarial robustness

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EDFAR - Exploring Data Augmentation For Adversarial Robustness

Applications of Machine Learning in Cybersecurity

These notebooks contain data for our reseach project, we are studying the effects of Data Augmentation on Adversial Robustness.

The techniques we are using can be catagorized into two broad catagories: Data Augmentation and Data Corruption.

Along with these techniques we also ran each iteration with Pad/Crop/Flip which are labelled as pcf to see results with combining augmentations.

Corrupted dataset can be found here: https://drive.google.com/drive/folders/1hDee1gmkv4JwF62FOJKRrwE9R5MXo_er?usp=sharing

How to reproduce results?

You can run the notebooks present in the folders. Preprocessed corrupted data can be found in the link given above.

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This is the repo for exploring data augmentation for adversarial robustness

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