论文标题
Deeprobust：用于对抗攻击和防御的Pytorch库
DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
论文作者
论文摘要
DeepRobust是一个Pytorch对抗学习库，旨在建立一个综合且易于使用的平台来培养该研究领域。它目前在图像域中包含10多种攻击算法和8种防御算法，在图形域中，在各种深度学习体系结构下，在图形域中包含9种攻击算法和4种防御算法。在本手册中，我们介绍了DeepRobust的主要内容，并提供了详细的说明。该库保留更新，可以在https://github.com/dse-msu/deeprobust上找到。
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.
