Improving the Transferability of Adversarial Samples by Path-Augmented Method
Author:
Affiliation:
1. The Chinese University of Hong Kong,Department of Computer Science and Engineering
2. School of Software Engineering, Sun Yat-sen University
3. Huawei Singular Security Lab,Beijing,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10203037/10203050/10203651.pdf?arnumber=10203651
Reference47 articles.
1. Deep Residual Learning for Image Recognition
2. Admix: Enhancing the Transferability of Adversarial Attacks
3. Simple black-box adversarial attacks;guo;International Conference on Machine Learning,2019
4. Enhancing the Transferability of Adversarial Attacks through Variance Tuning
5. AEON: a method for automatic evaluation of NLP test cases
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