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Machine learning attacks against the Asirra CAPTCHA
Proceedings of the 5th Symposium on Usable Privacy and Security - SOUPS '09
The Asirra CAPTCHA  , proposed at ACM CCS 2007, relies on the problem of distinguishing images of cats and dogs (a task that humans are very good at). The security of Asirra is based on the presumed difficulty of classifying these images automatically. In this paper, we describe a classifier which is 82.7% accurate in telling apart the images of cats and dogs used in Asirra. This classifier is a combination of support-vector machine classifiers trained on color and texture features extracteddoi:10.1145/1572532.1572585 dblp:conf/soups/Golle09 fatcat:5wz2tvvavfd3nihaffhpeajnna