Exploring the influence of CAPTCHA types to the users response time by statistical analysis

CAPTCHA stands for Completely Automated Public Turing Test to Tell Computers and Humans Apart. It is a test program that solves a given task for preventing the attacks made by automatic programs. If the response to CAPTCHA is correct, then the program classifies the user as a human. This paper introduces a new analysis of the impact of different CAPTCHAs to the Internet user’s response time. It overcomes the limitations of the previous approaches in the state-of-the-art. In this sense, different types of CAPTCHAs are presented and described. Furthermore, an experiment is conducted, which is based on two populations of Internet users for text and image-based CAPTCHA types, differentiated by demographic features, such as age, gender, education level and Internet experience. Each user is required to solve the different types of CAPTCHA, and the response time to solve the CAPTCHAs is registered. The obtained results are statistically processed by Mann-Whitney U and Pearson’s correlation coefficient tests. They analyze 7 different hypotheses which evaluate the response time in dependence of gender, age, education level and Internet experience, for the different CAPTCHA types. It represents an invaluable study in the literature to predict the best use of a given CAPTCHA for specific types of Internet users.