Adversarial Attack and Defense on Natural Language Processing in Deep Learning: A Survey and Perspective-Reference-Cited by-同舟云学术

Adversarial Attack and Defense on Natural Language Processing in Deep Learning: A Survey and Perspective

Published:2023 Issue: Volume: Page:409-424
ISSN:0302-9743
Container-title:Machine Learning for Cyber Security
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Author:

Dong Huoyuan,Dong Jialiang,Yuan Shuai,Guan Zhitao

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-20096-0_31

Reference43 articles.

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3. Wenqi, W., Lina, W., Benxiao, T., et al.: Towards a robust deep neural network in text domain: a survey. arXiv preprint arXiv:1902.07285 (2019)

4. Zhang, W., Sheng, Q., Alhazmi, A., et al.: Adversarial attacks on deep-learning models in natural language processing: a survey. ACM Trans. Intell. Syst. Technol. 11(3), 24:1–24:41 (2020)

5. Kusner, M., Sun, Y., Kolkin, N., et al.: From word embeddings to document distances. In: Proceedings of the International Conference on Machine Learning, Lille, pp. 957–966. ACM (2015)

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