Reading the moving text in animated text-based CAPTCHAs

Abstract

Having based on hard AI problems, CAPTCHA (Completely Automated Public Turing test to tell the Computers and Humans Apart) is a hot research topic in the field of computer vision and artificial intelligence. CAPTCHA is a challenge-response test conducted to single out humans and bots. It is ubiquitously implemented on the web since its introduction. As text-based CAPTCHAs are successfully broken by various researchers therefore several design variants have been proposed and implemented in order to further strengthen it. Animated Text-based CAPTCHAs are one of the design variant of it and are based on the difficulty of reading the moving text. They are based on zero knowledge per frame principle. Although it's still easy for humans to read animated text but it's a challenge for machines. As proposals for animated CAPTCHAs are on the rise so there is a strong need to scrutinize their strength against automated attacks. In this research, such CAPTCHAs are investigated to verify their robustness against automated attacks. The proposed methods proved that these CAPTCHAs are vulnerable and they do not guarantee the robustness against automated attacks. The proposed frame selection, noise removal, segmentation and recognition methods have successfully decoded these CAPTCHAs with an overall precision, segmentation accuracy and recognition rate of up to 53.8%, 92.9% and 93.5% respectively.