Towards Evaluating the Robustness of Adversarial Attacks Against Image Scaling Transformation-Reference-Cited by-同舟云学术

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Towards Evaluating the Robustness of Adversarial Attacks Against Image Scaling Transformation

Published:2023-01 Issue:1 Volume:32 Page:151-158
ISSN:2075-5597
Container-title:Chinese Journal of Electronics
language:
Short-container-title:Chinese J. Elect.

Author:

Zheng Jiamin¹,Zhang Yaoyuan²,Li Yuanzhang²,Wu Shangbo²,Yu Xiao³

Affiliation:

1. School of E-Business and Logistics, Beijing Technology and Business University,Beijing,China,100048

2. School of Computer Science and Technology, Beijing Institute of Technology,Beijing,China,100081

3. School of Computer Science and Technology, Shandong University of Technology,Shandong,China,255000

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/9970761/10038784/10038804.pdf?arnumber=10038804

Reference19 articles.

1. Understanding security failures of multi-factor authentication schemes for multi-server environments

2. Improving Transferability of Adversarial Examples With Input Diversity

3. Benchmarking Adversarial Robustness on Image Classification

4. Targeted adversarial examples generating method based on cVAE in black box settings;yu;Chinese Journal of Electronics,2021

5. Theoretically principled trade-off between robustness and accuracy;zhang;Proceedings of the 36th International Conference on Machine Learning,2019

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1. Attribution guided purification against adversarial patch;Displays;2024-07

2. DFaP: Data Filtering and Purification Against Backdoor Attacks;Lecture Notes in Computer Science;2024

3. Assessment and Evaluation of Deep Brain Stimulation Surgery Utilizing Convolutional Neural Networks in the Context of Adversarial Attack Strategies;2023 International Conference on Emerging Research in Computational Science (ICERCS);2023-12-07

4. A Streamlined Framework of Metamorphic Malware Classification via Sampling and Parallel Processing;Electronics;2023-10-27

5. Multimodel Collaboration to Combat Malicious Domain Fluxing;Electronics;2023-10-02

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