OpenAttack: An Open-source Textual Adversarial Attack Toolkit

Guoyang Zeng, Fanchao Qi, Qianrui Zhou, Tingji Zhang, Zixian Ma, Bairu Hou, Yuan Zang, Zhiyuan Liu, Maosong Sun


Abstract
Textual adversarial attacking has received wide and increasing attention in recent years. Various attack models have been proposed, which are enormously distinct and implemented with different programming frameworks and settings. These facts hinder quick utilization and fair comparison of attack models. In this paper, we present an open-source textual adversarial attack toolkit named OpenAttack to solve these issues. Compared with existing other textual adversarial attack toolkits, OpenAttack has its unique strengths in support for all attack types, multilinguality, and parallel processing. Currently, OpenAttack includes 15 typical attack models that cover all attack types. Its highly inclusive modular design not only supports quick utilization of existing attack models, but also enables great flexibility and extensibility. OpenAttack has broad uses including comparing and evaluating attack models, measuring robustness of a model, assisting in developing new attack models, and adversarial training. Source code and documentation can be obtained at https://github.com/thunlp/OpenAttack.
Anthology ID:
2021.acl-demo.43
Volume:
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
363–371
Language:
URL:
https://aclanthology.org/2021.acl-demo.43
DOI:
10.18653/v1/2021.acl-demo.43
Bibkey:
Cite (ACL):
Guoyang Zeng, Fanchao Qi, Qianrui Zhou, Tingji Zhang, Zixian Ma, Bairu Hou, Yuan Zang, Zhiyuan Liu, and Maosong Sun. 2021. OpenAttack: An Open-source Textual Adversarial Attack Toolkit. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: System Demonstrations, pages 363–371, Online. Association for Computational Linguistics.
Cite (Informal):
OpenAttack: An Open-source Textual Adversarial Attack Toolkit (Zeng et al., ACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.acl-demo.43.pdf
Code
 thunlp/OpenAttack
Data
SST