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Robust Text CAPTCHAs Using Adversarial Examples

Published:2022-12-17 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE International Conference on Big Data (Big Data)
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Author:

Shao Rulin¹,Shi Zhouxing²,Yi Jinfeng³,Chen Pin-Yu⁴,Hsieh Cho-Jui²

Affiliation:

1. Carnegie Mellon University,Machine Learning Department,Pittsburgh,United States

2. University of California, Los Angeles,Computer Science Department,Los Angeles,United States

3. Jd.Com, Inc.,JD AI Research,Shanghai,China

4. IBM,IBM Research,New York,United States

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10020192/10020156/10021100.pdf?arnumber=10021100

Reference35 articles.

1. Boosting Adversarial Attacks with Momentum

2. Densely connected convolutional networks;huang;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition,2017

3. Adversarial machine learning at scale;kurakin,2016

4. Deep Residual Learning for Image Recognition

5. Thermometer encoding: One hot way to resist adversarial examples;buckman;International Conference on Learning Representations,2018

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Adversarial Machine Learning for Social Good: Reframing the Adversary as an Ally;IEEE Transactions on Artificial Intelligence;2024-09

2. Lightweight Privacy Protection via Adversarial Sample;Electronics;2024-03-26

3. Image CAPTCHAs: When Deep Learning Breaks the Mold;IEEE Access;2024

4. Farsi CAPTCHA Recognition Using Attention-Based Convolutional Neural Network;2023 9th International Conference on Web Research (ICWR);2023-05-03

5. A Survey on Adversarial Perturbations and Attacks on CAPTCHAs;Applied Sciences;2023-04-05

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