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Handwritten CAPTCHA recognizer: a text CAPTCHA breaking method based on style transfer network
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DOI：10.1007/s11042-021-11485-9.png)
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摘要
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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.
Keyword:
Big multimedia data Security
Text CAPTCHA breaking
Style transfer network
Handwritten
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期刊
IF:
3
论文数:
2.0W
被引数:
3.2W
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