DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
Abstract
DeepRobust is a PyTorch library offering a comprehensive platform for adversarial learning with diverse attack and defense algorithms across image and graph domains.
DeepRobust is a PyTorch adversarial learning library which aims to build a comprehensive and easy-to-use platform to foster this research field. It currently contains more than 10 attack algorithms and 8 defense algorithms in image domain and 9 attack algorithms and 4 defense algorithms in graph domain, under a variety of deep learning architectures. In this manual, we introduce the main contents of DeepRobust with detailed instructions. The library is kept updated and can be found at https://github.com/DSE-MSU/DeepRobust.
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