Abstract
Text based CAPTCHAs are ubiquitous on the Internet since they are easily generated by machines, easily solvable by humans and yet not easily defeated by state-of-the-art computer algorithms. Over the years, several attacks have been designed by researchers to solve different types of CAPTCHAs. These attacks always assume that the type of CAPTCHA is known. However, in order to devise a common frame work, comprising of different attacks that can be launched automatically, the first prime step is to recognize the CAPTCHA scheme. In this paper we present a method based on geometric features to automatically identify text based CAPTCHA schemes. The proposed method is verified on a data set comprising of 25 different types of CAPTCHA (1,000 samples per type). We achieve an identification / classification accuracy of up to approximately 99%.
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Jalwana, M.A.A.K., Khan, M.M., Ilyas, M.U. (2014). Automatic Identification of CAPTCHA Schemes. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2014. Lecture Notes in Computer Science, vol 8888. Springer, Cham. https://doi.org/10.1007/978-3-319-14364-4_40
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DOI: https://doi.org/10.1007/978-3-319-14364-4_40
Publisher Name: Springer, Cham
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