Boosting the Transferability of Adversarial Attacks With Frequency-Aware Perturbation

Author:

Wang Yajie1ORCID,Wu Yi2ORCID,Wu Shangbo1,Liu Ximeng3ORCID,Zhou Wanlei4ORCID,Zhu Liehuang1ORCID,Zhang Chuan1ORCID

Affiliation:

1. School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China

2. Academy of Information and Communications Technology, Beijing, China

3. College of Computer and Data Science, Fuzhou University, Fuzhou, China

4. Faculty of Data Science, City University of Macau, Macau, China

Funder

National Key Research and Development Program of China

Postdoctoral Fellowship Program of China Postdoctoral Science Foundation

CPSF

National Natural Science Foundation of China

Open Project Funding of Key Laboratory of Mobile Application Innovation and Governance Technology, Ministry of Industry and Information Technology

Beijing Institute of Technology Research Fund Program for Young Scholars

Young Elite Scientists Sponsorship Program

China Association for Science and Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Reference42 articles.

1. An image is worth 16×16 words: Transformers for image recognition at scale;Dosovitskiy;arXiv:2010.11929,2020

2. Swin Transformer: Hierarchical Vision Transformer using Shifted Windows

3. MLP-mixer: An all-MLP architecture for vision;Tolstikhin

4. Delving into transferable adversarial examples and black-box attacks;Liu;arXiv:1611.02770,2016

5. Explaining and harnessing adversarial examples;Goodfellow;arXiv:1412.6572,2015

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