Multi-Modal CAPTCHA: A User Verification Scheme

Abstract

CAPTCHA is an automated test that humans can pass, but current computer programs can't pass any program that has high success over a CAPTCHA can be used to solve an unsolved Artificial Intelligence (AI) problem. The most widely used CAPTCHAs rely on the sophisticated distortion of text images rendering them unrecognizable to the state of the art of pattern recognition techniques, and these text-based schemes have found widespread applications in commercial websites like free email service providers, social networking sites and online auction sites. The increase in bots breaking CAPTCHAs shows the ineffectiveness of the text-based CAPTCHAs that are used on most websites and Webmail services today. Bots can easily read the distorted letters and words using optical character recognition (OCR) or break the CAPTCHA using a dictionary attack. The weakness of each CAPTCHA scheme is summarized; accordingly we make an approach to build our CAPTCHA method. Considering the case study results and including other points which may pose difficulty for the OCR systems,we proposed a new technique to build a CAPTCHA which is multi-modal (Picture and Text based). An image is being rendered on the screen and many text labels drawn over it. A user has to identify the correct name of the underlying image among the set of text labels that are scattered over it, in order to pass a human verification test. We also proposed to use cursive text instead of plain text labels.