Framework for evaluation of text captchas
WWW (Companion Volume)(2013)
摘要
Interactive websites use text-based Captchas to prevent unauthorized automated interactions. These Captchas must be easy for humans to decipher while being difficult to crack by automated means. In this work we present a framework for the systematic study of Captchas along these two competing objectives. We begin by abstracting a set of distortions that characterize current and past commercial text-based Captchas. By means of user studies, we quantify the way human Captcha solving performance varies with changes in these distortion parameters. To quantify the effect of these distortions on the accuracy of automated solvers (bots), we propose a learning-based algorithm that performs automated Captcha segmentation driven by character recognition. Results show that our proposed algorithm is generic enough to solve text-based Captchas with widely varying distortions without requiring the use of hand-coded image processing or heuristic rules.
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关键词
captcha segmentation,past commercial text-based captchas,human captcha,character recognition,automated mean,learning-based algorithm,proposed algorithm,text-based captchas,unauthorized automated interaction,text captchas,automated solvers,captcha
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