A Novel Animated CAPTCHA Technique based on Persistence of Vision

Abstract

Image-based CAPTCHA challenges have been successfully used to distinguish between humans and bots for a long time. However, image-based CAPTCHA techniques are constantly broken by hackers, forcing web developers to implement more robust security features and new approaches in CAPTCHA images. Modern-day bots can use many techniques and technologies to break CAPTCHA images automatically. These techniques include OCR, Segmentation, erosion, threshold, flood fill, etc. This led to innovative CAPTCHA systems, including those based on drag and drop, image recognition, fingerprint, mathematical problems, etc. Animated image CAPTCHAs have also been designed to show moving characters and objects and require users to recognize the characters or objects in the animation. Unfortunately, these CAPTCHA systems have also been broken successfully. This research proposes a novel animated CAPTCHA technique based on the persistence of vision, which shows text characters in multiple layers in an animated image. The proposed CAPTCHA technique has been implemented in PHP using GD library functions and tested using various popular CAPTCHA breaking tools. Further, the proposed CAPTCHA challenge has also been tested against the frame separation based breaking technique. The security analysis and usability study have demonstrated user-friendliness, vast accessibility, and robustness.