Enhancing Transferability of Adversarial Examples Through Mixed-Frequency Inputs-Reference-Cited by-同舟云学术

Enhancing Transferability of Adversarial Examples Through Mixed-Frequency Inputs

Author:

Qian Yaguan¹^ORCID,Chen Kecheng¹^ORCID,Wang Bin²,Gu Zhaoquan³^ORCID,Ji Shouling⁴^ORCID,Wang Wei⁵^ORCID,Zhang Yanchun⁶^ORCID

Affiliation:

1. School of Big-Data Science, Zhejiang University of Science and Technology, Hangzhou, China

2. Zhejiang Key Laboratory of Artificial Intelligence of Things (AIoT) Network and Data Security, Hangzhou, China

3. College of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China

4. School of Computer Science and Technology, Zhejiang University, Hangzhou, China

5. Ministry of Education Key Laboratory for Intelligent Networks and Network Security, Xi’an Jiaotong University, Xi’an, China

6. School of Computer Science and Technology, Zhejiang Normal University, Jinhua, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Zhejiang Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

Reference57 articles.

2. Intriguing properties of neural networks;Szegedy

3. Explaining and harnessing adversarial examples;Goodfellow