Handwritten CAPTCHA recognizer: a text CAPTCHA breaking method based on style transfer network

被引:1
|
作者
Chen, Jun [1 ]
Luo, Xiangyang [2 ]
Zhu, Liyan [2 ]
Zhang, Qikun [3 ]
Gan, Yong [3 ]
机构
[1] Nanjing Sport Inst, Nanjing, Peoples R China
[2] State Key Lab Math Engn & Adv Comp, Zhengzhou, Peoples R China
[3] Zhengzhou Univ Light Ind, Zhengzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Big multimedia data Security; Text CAPTCHA breaking; Style transfer network; Handwritten; Print;
D O I
10.1007/s11042-021-11485-9
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The CAPTCHA technology can be used to ensure big multimedia data security, which includes CAPTCHA design and CAPTCHA recognition. For the existing methods are difficult to achieve high breaking accuracy for complex handwritten text CAPTCHA, a handwritten CAPTCHA recognizer is proposed, which is a text CAPTCHA breaking method based on style transfer network. Firstly, different from the traditional viewpoints that font structure and font style of characters are inseparable in this field, a new idea of separating font structure and font style of characters is proposed, and it is pointed out that character recognition mainly depends on font structure rather than font style. Secondly, based on this idea, a style transfer network for text CAPTCHA is constructed to convert complex and variable handwritten CAPTCHA into easy-to-recognize printed CAPTCHA. Finally, based on deep convolutional neural network, a text CAPTCHA recognition network is constructed to identify the converted printed CAPTCHAs. With CAPTCHAs from three real websites: eBay, Google and reCAPTCHA, experimental results show that the recognizer has higher breaking accuracy for handwritten CAPTCHA compared with the methods proposed in NDSS'16, CCS'18 and "Science" in 2017.
引用
收藏
页码:13025 / 13043
页数:19
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