Vulnerability analysis of captcha using Deep learning

arXiv:2302.09389v2 Announce Type: replace-cross
Abstract: Several websites improve their security and avoid dangerous Internet attacks by implementing CAPTCHAs (Completely Automated Public Turing test to tell Computers and Humans Apart), a type of verification to identify whether the end-user is human or a robot. The most prevalent type of CAPTCHA is text-based, designed to be easily recognized by humans while being unsolvable towards machines or robots. However, as deep learning technology progresses, development of convolutional neural network (CNN) models that predict …

abstract analysis arxiv attacks automated captcha computers cs.ai cs.cr cs.cv cs.lg deep learning human humans identify internet public robot security test text the end turing turing test type verification vulnerability websites