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End-to-end attack on text-based CAPTCHAs based on cycle-consistent generative adversarial network

  • Published:2021-04 Issue: Volume:433 Page:223-236
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Li Chunhui,Chen Xingshu,Wang Haizhou,Wang Peiming,Zhang Yu,Wang Wenxian

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference46 articles.

1. Securing online social networks against bad bots based on a necklace captcha approach;Torky,2016

2. Search prevention with captcha against web indexing: A proof of concept;Kim,2019

3. Tell me about yourself: The malicious captcha attack;Gelernter,2016

4. Research on deep learning techniques in breaking text-based captchas and designing image-based captcha;Tang;IEEE Transactions on Information Forensics and Security (TIFS),2018

5. Hitting three birds with one system: A voice-based captcha for the modern user;Shah,2018

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1. Transformer-based end-to-end attack on text CAPTCHAs with triplet deep attention;Computers & Security;2024-11

2. Exploring self-supervised learning in Multiview captcha recognition;2023 IEEE 20th India Council International Conference (INDICON);2023-12-14

3. Extended Research on the Security of Visual Reasoning CAPTCHA;IEEE Transactions on Dependable and Secure Computing;2023-11

4. Fighting Attacks on Large Character Set CAPTCHAs Using Transferable Adversarial Examples;2023 International Joint Conference on Neural Networks (IJCNN);2023-06-18

5. GeeSolver: A Generic, Efficient, and Effortless Solver with Self-Supervised Learning for Breaking Text Captchas;2023 IEEE Symposium on Security and Privacy (SP);2023-05
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