zxCAPTCHA: New Security-Enhanced CAPTCHA

Nghia Dinh, Trung Nguyen, Vinh Truong Hoang
{"title":"zxCAPTCHA: New Security-Enhanced CAPTCHA","authors":"Nghia Dinh, Trung Nguyen, Vinh Truong Hoang","doi":"10.1109/KST57286.2023.10086931","DOIUrl":null,"url":null,"abstract":"Automated attacks using CNN (Convolutional Neural Network), ML (Machine Learning), and DNN (Deep Neural Network have been successful in bypassing traditional CAPTCHAs. However, Deep Learning techniques, adversarial examples and style neural transfer, have been shown to be particularly effective in protecting CAPTCHAs. In this study, the authors proposed zxCAPTCHA, a new CAPTCHA that combines cognitive-based, image-based, and text-based CAPTCHA characteristics with Deep Learning techniques to improve security. Extensive evaluations were conducted to assess the improvement of the CAPTCHA security. The experiment shows that zxCAPTCHA considerably enhances the security while maintaining comparable usability. We also demonstrate the effectiveness of combining cognitive techniques and Deep Learning to improve CAPTCHA security.","PeriodicalId":351833,"journal":{"name":"2023 15th International Conference on Knowledge and Smart Technology (KST)","volume":"655 2","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 15th International Conference on Knowledge and Smart Technology (KST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KST57286.2023.10086931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Automated attacks using CNN (Convolutional Neural Network), ML (Machine Learning), and DNN (Deep Neural Network have been successful in bypassing traditional CAPTCHAs. However, Deep Learning techniques, adversarial examples and style neural transfer, have been shown to be particularly effective in protecting CAPTCHAs. In this study, the authors proposed zxCAPTCHA, a new CAPTCHA that combines cognitive-based, image-based, and text-based CAPTCHA characteristics with Deep Learning techniques to improve security. Extensive evaluations were conducted to assess the improvement of the CAPTCHA security. The experiment shows that zxCAPTCHA considerably enhances the security while maintaining comparable usability. We also demonstrate the effectiveness of combining cognitive techniques and Deep Learning to improve CAPTCHA security.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
zxCAPTCHA:新的安全增强的验证码
使用CNN(卷积神经网络)、ML(机器学习)和DNN(深度神经网络)的自动攻击已经成功绕过了传统的验证码。然而,深度学习技术,对抗性示例和风格神经转移,已被证明在保护captcha方面特别有效。在这项研究中,作者提出了zxCAPTCHA,这是一种新的CAPTCHA,将基于认知、基于图像和基于文本的CAPTCHA特征与深度学习技术相结合,以提高安全性。进行了广泛的评估,以评估CAPTCHA安全性的改进。实验表明,在保持可用性的同时,zxCAPTCHA大大提高了安全性。我们还展示了将认知技术与深度学习相结合以提高CAPTCHA安全性的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
An Efficient Medical Records Access Control with Auditable Outsourced Encryption and Decryption Analysis of Defect Associated with Powder Bed Fusion with Deep Learning and Explainable AI Question Classification for Thai Conversational Chatbots Using Artificial Neural Networks and Multilingual BERT Models LightPEN: Optimizing the Vulnerability Exposures for Lightweight Penetration Test WAFL-GAN: Wireless Ad Hoc Federated Learning for Distributed Generative Adversarial Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1