DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses
Abstract
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.
- Publication:
-
arXiv e-prints
- Pub Date:
- May 2020
- DOI:
- 10.48550/arXiv.2005.06149
- arXiv:
- arXiv:2005.06149
- Bibcode:
- 2020arXiv200506149L
- Keywords:
-
- Computer Science - Machine Learning;
- Computer Science - Cryptography and Security;
- Statistics - Machine Learning
- E-Print:
- Adversarial attacks and defenses, Pytorch library