An improved text-based and image-based CAPTCHA based on solving and response time

Abstract

CAPTCHA is an acronym that stands for Completely Automated Public Turing Test to tell Computers and Humans Apart (CAPTCHA), it is a good example of an authentication system that can be used to determine the true identity of any user. It serves as a security measure to prevent an attack caused by web bots (automatic programs) during an online transaction. It can come as text-based or image-based depending on the project and the programmer. The usability and robustness, as well as level of security, provided each of the varies and call for the development of an improved system. Hence, this paper studied and improved two different CAPTCHA systems (the text-based CAPTCHA and image-based CAPTCHA). The text-based and image-based CAPTCHA were designed using JavaScript. Response time and solving time are the two metrics used to determine the effectiveness and efficiency of the two CAPTCHA systems. The inclusion of response time and solving time improved the shortfall of the usability and robustness of the existing system. The developed system was tested using 200 students from the Federal College of Animal Health and Production Technology. The results of each of the participants, for the two CAPTCHAs, were extracted from the database and subjected to analysis using SPSS. The result shows that text-based CAPTCHA has the lowest average solving time (21.3333 s) with a 47.8% success rate while image-based CAPTCHA has the highest average solving time was 23.5138 s with a 52.8% success rate. The average response time for the image-based CAPTCHA was 2.1855 s with a 37.9% success rate lower than the text-based CAPTCHA response time (3.5561 s) with a 62.1% success rate. This indicates that the text-based CAPTCHA is more effective in terms of usability tests while image-based CAPTCHA is more efficient in terms of system responsiveness and recommended for potential users.