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Predicting the Usability of the Dice CAPTCHA via Artificial Neural Network

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 988))

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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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Notes

  1. 1.

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

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Acknowledgments

This work was partially supported by the Mathematical Institute of the Serbian Academy of Sciences and Arts (Project III44006). The authors are fully grateful to the participants to the experiment for anonymously providing their data. This paper is dedicated to our colleague and friend Associate Professor Darko Brodić with full gratitude.

Author information

Authors and Affiliations

  1. University of Calabria, DIMES, Rende, CS, Italy

    Alessia Amelio

  2. Mathematical Institute of the S.A.S.A., Belgrade, Serbia

    Radmila Janković

  3. University of Belgrade, Technical Faculty in Bor, Bor, Serbia

    Dejan Tanikić

  4. Technical University of Sofia, Department of Radio Communications and Video Technologies, Sofia, Bulgaria

    Ivo Rumenov Draganov

Authors
  1. Alessia Amelio
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  2. Radmila Janković
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  3. Dejan Tanikić
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  4. Ivo Rumenov Draganov
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Corresponding author

Correspondence to Alessia Amelio .

Editor information

Editors and Affiliations

  1. Italian National Research Council, Pisa, Italy

    Paolo Manghi

  2. Italian National Research Council, Pisa, Italy

    Leonardo Candela

  3. University of Padua, Padua, Italy

    Gianmaria Silvello

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Amelio, A., Janković, R., Tanikić, D., Draganov, I.R. (2019). Predicting the Usability of the Dice CAPTCHA via Artificial Neural Network. In: Manghi, P., Candela, L., Silvello, G. (eds) Digital Libraries: Supporting Open Science. IRCDL 2019. Communications in Computer and Information Science, vol 988. Springer, Cham. https://doi.org/10.1007/978-3-030-11226-4_4

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  • DOI: https://doi.org/10.1007/978-3-030-11226-4_4

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-11225-7

  • Online ISBN: 978-3-030-11226-4

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