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Analysis of Usability for the Dice CAPTCHA

1
Department of Computer Engineering, Modeling, Electronics and Systems (DIMES), University of Calabria, 87036 Rende (CS), Italy
2
Department of Radio Communications and Video Technology, Technical University of Sofia, 1756 Sofia, Bulgaria
3
Mathematical Institute of Serbian Academy of Sciences and Arts, 11000 Belgrade, Serbia
4
Technical Faculty in Bor, University of Belgrade, 19210 Bor, Serbia
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Information 2019, 10(7), 221; https://doi.org/10.3390/info10070221
Received: 15 June 2019 / Revised: 23 June 2019 / Accepted: 24 June 2019 / Published: 26 June 2019
(This article belongs to the Special Issue Artificial Intelligence—Methodology, Systems, and Applications)
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Abstract

This paper explores the usability of the Dice CAPTCHA via analysis of the time spent to solve the CAPTCHA, and number of tries for solving the CAPTCHA. The experiment was conducted on a set of 197 subjects who use the Internet, and are discriminated by age, daily Internet usage in hours, Internet experience in years, and type of device where a solution to the CAPTCHA is found. Each user was asked to find a solution to the Dice CAPTCHA on a tablet or laptop, and the time to successfully find a solution to the CAPTCHA for a given number of attempts was registered. Analysis was performed on the collected data via association rule mining and artificial neural network. It revealed that the time to find a solution in a given number of attempts of the CAPTCHA depended on different combinations of values of user’s features, as well as the most meaningful features influencing the solution time. In addition, this dependence was explored through prediction of the CAPTCHA solution time from the user’s features via artificial neural network. The obtained results are very helpful to analyze the combination of features having an influence on the CAPTCHA solution, and consequently, to find the CAPTCHA mostly complying to the postulate of “ideal” test. View Full-Text
Keywords: human-computer interaction; Dice CAPTCHA; association rule mining; feedforward neural network human-computer interaction; Dice CAPTCHA; association rule mining; feedforward neural network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Amelio, A.; Draganov, I.R.; Janković, R.; Tanikić, D. Analysis of Usability for the Dice CAPTCHA. Information 2019, 10, 221.

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