OTRCaptcha: A Novel Object and Text Recognition Based Image CAPTCHA

CAPTCHA is an important technology to prevent auto-script attack. Currently most of the CAPTCHA systems are text based, which firstly distort, rotate different characters and then use some obfuscation, aiming to make the text difficult to be recognized by autoscript while still can be learnt easily by real users. However, such kind of CAPTCHA schema either too simple, which can be attacked easily by using optimal character recognition (OCR) or machine learning based technology, or it is too complex that even real users cannot tell it. By observing such contradiction between security and usability, we propose a novel object and text recognition based image CAPTCHA system called OTRCaptcha. In OTRCaptcha, some object images (each has a label) and their names are attached into a background image respectively. In order to pass this CAPTCHA, users have to identify all the object images, labels within those objects and their names. Besides, users also need to identify the semantic relationship between object and its name. Both the theoretical analysis and experiment result show that OTRCapthcha can provide both high security and strong usability.