Applying Visual Cryptography to Enhance Text Captchas

Xuehu Yan, Feng Liu, Wei Qi Yan and Yuliang Lu
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Xuehu Yan: National University of Defense Technology, Hefei 230037, China
Feng Liu: National University of Defense Technology, Hefei 230037, China
Wei Qi Yan: Auckland University of Technology, Auckland 1142, New Zealand
Yuliang Lu: National University of Defense Technology, Hefei 230037, China

Mathematics, 2020, vol. 8, issue 3, 1-13

Abstract: Nowadays, lots of applications and websites utilize text-based captchas to partially protect the authentication mechanism. However, in recent years, different ways have been exploited to automatically recognize text-based captchas especially deep learning-based ways, such as, convolutional neural network (CNN). Thus, we have to enhance the text captchas design. In this paper, using the features of the randomness for each encoding process in visual cryptography (VC) and the visual recognizability with naked human eyes, VC is applied to design and enhance text-based captcha. Experimental results using two typical deep learning-based attack models indicate the effectiveness of the designed method. By using our designed VC-enhanced text-based captcha (VCETC), the recognition rate is in some degree decreased.

Keywords: text captcha; visual cryptography; random grids; visual cryptography application; enhanced text captcha (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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