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2019 | OriginalPaper | Buchkapitel

Predicting the Usability of the Dice CAPTCHA via Artificial Neural Network

verfasst von : Alessia Amelio, Radmila Janković, Dejan Tanikić, Ivo Rumenov Draganov

Erschienen in: Digital Libraries: Supporting Open Science

Verlag: Springer International Publishing

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Abstract

This paper introduces a new study of the CAPTCHA usability which analyses the predictability of the solution time, also called response time, to solve the Dice CAPTCHA. This is accomplished by proposing a new artificial neural network model for predicting the response time from known personal and demographic features of the users who solve the CAPTCHA: (i) age, (ii) device on which the CAPTCHA is solved, and (iii) Web use in years. The experiment involves a population of 197 Internet users, who is required to solve two types of Dice CAPTCHA on laptop or tablet computer. The data collected from the experiment is subject to the artificial neural network model which is trained and tested to predict the response time. The proposed analysis provides new results of usability of the Dice CAPTCHA and important suggestions for designing new CAPTCHAs which could be closer to an “ideal” CAPTCHA.

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The gathered data is freely available at: https://sites.google.com/site/alessiaamelio/ software-tools/dice-captcha-dataset.

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Titel: Predicting the Usability of the Dice CAPTCHA via Artificial Neural Network
verfasst von: Alessia Amelio
Radmila Janković
Dejan Tanikić
Ivo Rumenov Draganov
Verlag: Springer International Publishing
Buch: Digital Libraries: Supporting Open Science
Print ISBN: 978-3-030-11225-7

Electronic ISBN: 978-3-030-11226-4

Copyright-Jahr: 2019
DOI: https://doi.org/10.1007/978-3-030-11226-4_4

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