Predicting the Usability of the Dice CAPTCHA via Artificial Neural Network

  • Alessia AmelioEmail author
  • Radmila Janković
  • Dejan Tanikić
  • Ivo Rumenov Draganov
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 988)


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.


Prediction CAPTCHA Usability 



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.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of Calabria, DIMESRendeItaly
  2. 2.Mathematical Institute of the S.A.S.A.BelgradeSerbia
  3. 3.University of Belgrade, Technical Faculty in BorBorSerbia
  4. 4.Technical University of Sofia, Department of Radio Communications and Video TechnologiesSofiaBulgaria

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