Cracking Captcha Completely Automated Public Turing Test to Tell Computers and Humans Apart

Abstract

Completely Automated Public Turing Tests to Tell Computers and Humans Apart (CAPTCHAs) are the automatic filters that are widely used these days to disallow any automated script that can perform the work of a human. CAPTCHAs are built in such a way that it is very difficult for any automated script to break them. The state of the art of CAPTCHA design suggests that such text-based schemes should rely on segmentation resistance to provide security guarantee, as individual character recognition after segmentation can be solved with a high success rate by standard methods such as neural networks. We analyse the security of a text-based CAPTCHAs and the loopholes in designing of these captchas. Defeating a CAPTCHA test requires two procedures: segmentation and recognition. In this project, an approach to break text based CAPTCHAs has been proposed that first preprocesses the given CAPTCHA, segments its characters, and then recognizes the characters depending on it‟s features. The breaking of CAPTCHAs give strength to CAPTCHAs which in turn help to develop more robust CAPTCHAs.