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International Workshop on Multi-disciplinary Trends in Artificial Intelligence

MIWAI 2017: Multi-disciplinary Trends in Artificial Intelligence pp 252–265Cite as

Usability Analysis of the Image and Interactive CAPTCHA via Prediction of the Response Time

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10607))

Abstract

This paper introduces a new method for automatically predicting the response time of the Internet users to solve the CAPTCHA test by a regression tree strategy. The input to the model is a set of demographic features of the user: (i) age, (ii) education level, and (iii) Internet experience level. The experiment is performed on 114 Internet users who are invited to solve three image and interactive CAPTCHA tests: (i) FunCAPTCHA, (ii) home numbers, and (iii) picture of the CAPTCHA. Collected demographic features and response time for each user are processed by the regression tree approach in order to evaluate the prediction accuracy. Obtained results revealed the ability of the model in correctly predicting the response time of the specific CAPTCHA types. This represents an invaluable analysis in the state-of-the-art for designing new CAPTCHA types which are more accustomed to specific categories of Internet users.

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References

  1. Aggarwal, S.: Animated CAPTCHAs and games for advertising. In: Proceedings of the 22nd International Conference on World Wide Web, pp. 1167–1174. ACM (2013)

    Google Scholar 

  2. Ahn, L., Blum, M., Hopper, N.J., Langford, J.: CAPTCHA: using hard AI problems for security. In: Biham, E. (ed.) EUROCRYPT 2003. LNCS, vol. 2656, pp. 294–311. Springer, Heidelberg (2003). doi:10.1007/3-540-39200-9_18

    Chapter  Google Scholar 

  3. von Ahn, L., Blum, M., Langford, J.: Telling humans and computers apart automatically. Commun. ACM 47(2), 56–60 (2004)

    Article  Google Scholar 

  4. Baecher, P., Fischlin, M., Gordon, L., Langenberg, R., Ltzow, M., Schršder, D.: Captchas: the good, the bad, and the ugly. In: Freiling, F.C. (ed.) Sicherheit. LNI, vol. 170, pp. 353–365. GI (2010)

    Google Scholar 

  5. Brodić, D., Petrovska, S., Jevtić, M., Milivojević, Z.N.: The influence of the CAPTCHA types to its solving times. In: 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 1274–1277, May 2016

    Google Scholar 

  6. Brodić, D., Amelio, A.: Analysis of the human-computer interaction on the example of image-based CAPTCHA by association rule mining. In: Gamberini, L., Spagnolli, A., Jacucci, G., Blankertz, B., Freeman, J. (eds.) Symbiotic 2016. LNCS, vol. 9961, pp. 38–51. Springer, Cham (2017). doi:10.1007/978-3-319-57753-1_4

    Chapter  Google Scholar 

  7. Brodić, D., Amelio, A., Draganov, I.R.: Response time analysis of text-based CAPTCHA by association rules. In: Dichev, C., Agre, G. (eds.) AIMSA 2016. LNCS, vol. 9883, pp. 78–88. Springer, Cham (2016). doi:10.1007/978-3-319-44748-3_8

    Chapter  Google Scholar 

  8. Brodić, D., Amelio, A., Janković, R.: Exploring the influence of CAPTCHA types to the users response time by statistical analysis. Multimedia Tools Appl. 1–37 (2017). doi:10.1007/s11042-017-4883-7

  9. Bursztein, E., Bethard, S., Fabry, C., Mitchell, J.C., Jurafsky, D.: How good are humans at solving CAPTCHAs? A large scale evaluation. In: Proceedings of the 2010 IEEE Symposium on Security and Privacy, SP 2010, pp. 399–413. IEEE Computer Society, Washington, DC (2010)

    Google Scholar 

  10. Datta, R., Li, J., Wang, J.Z.: Imagination: a robust image-based CAPTCHA generation system. In: Proceedings of the 13th Annual ACM International Conference on Multimedia, pp. 331–334. ACM (2005)

    Google Scholar 

  11. Elson, J., Douceur, J.R., Howell, J., Saul, J.: Asirra: a CAPTCHA that exploits interest-aligned manual image categorization. In: ACM Conference on Computer and Communications Security, vol. 7, pp. 366–374. Citeseer (2007)

    Google Scholar 

  12. Gossweiler, R., Kamvar, M., Baluja, S.: What’s up CAPTCHA?: a CAPTCHA based on image orientation. In: Proceedings of the 18th International Conference on World Wide Web, pp. 841–850. ACM (2009)

    Google Scholar 

  13. Kim, J., Yang, J., Wohn, K.: Agecaptcha: an image-based captcha that annotates images of human faces with their age groups. TIIS 8(3), 1071–1092 (2014)

    Article  Google Scholar 

  14. Lee, Y.L., Hsu, C.H.: Usability study of text-based CAPTCHAs. Displays 32(2), 81–86 (2011)

    Article  Google Scholar 

  15. Lever, J., Krzywinski, M., Altman, N.: Points of significance: model selection and overfitting. Nat. Methods 13(9), 703–704 (2016)

    Article  Google Scholar 

  16. Lin, R., Huang, S.Y., Bell, G.B., Lee, Y.K.: A new CAPTCHA interface design for mobile devices. In: Proceedings of the Twelfth Australasian User Interface Conference vol. 117, pp. 3–8. Australian Computer Society, Inc. (2011)

    Google Scholar 

  17. Morgan, J.N., Sonquist, J.A.: Problems in the analysis of survey data, and a proposal. J. Am. Stat. Assoc. 58(302), 415–434 (1963)

    Article  MATH  Google Scholar 

  18. Nonparametric Supervised Learning: (2013). http://cda.psych.uiuc.edu/multivari ate_fall_2013/matlab_help/nonparametric_supervised_learning.pdf

  19. Rao, K., Sri, K., Sai, G.: A novel video CAPTCHA technique to prevent BOT attacks. Procedia Comput. Sci. 85, 236–240 (2016). International Conference on Computational Modelling and Security (CMS 2016)

    Google Scholar 

  20. Reshef, E., Raanan, G., Solan, E.: Method and system for discriminating a human action from a computerized action. Patent US20050114705, 1997, Pubblicated 26 May 2005 (2005)

    Google Scholar 

  21. Shirali-Shahreza, M., Shirali-Shahreza, S.: Drawing CAPTCHA. In: 2006 28th International Conference on Information Technology Interfaces, pp. 475–480. IEEE (2006)

    Google Scholar 

  22. Skrondal, A., Rabe-Hesketh, S.: Prediction in multilevel generalized linear models. J. Roy. Stat. Soc.: Ser. A (Stat. Soc.) 172(3), 659–687 (2009)

    Article  MathSciNet  Google Scholar 

  23. Turing, A.M.: Computers & thought. In: Feigenbaum, E.A., Feldman, J. (eds.) Computing Machinery and Intelligence, pp. 11–35. MIT Press, Cambridge (1995)

    Google Scholar 

  24. Wilkinson, L.: Tree structured data analysis: AID, CHAID and CART. In: Sawtooth/SYSTAT Joint Software Conference, Sun Valley, ID (1992)

    Google Scholar 

  25. Yadav, S., Shukla, S.: Analysis of k-fold cross-validation over hold-out validation on colossal datasets for quality classification. In: 2016 IEEE 6th International Conference on Advanced Computing (IACC), pp. 78–83, February 2016

    Google Scholar 

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Acknowledgments

The authors are fully grateful to the anonymous participants for publicly providing their data.

This work was partially supported by the Grant of the Ministry of Education, Science and Technological Development of the Republic of Serbia, as a part of the project TR33037.

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Authors and Affiliations

  1. Technical Faculty in Bor, University of Belgrade, V.J. 12, 19210, Bor, Serbia

    Darko Brodić

  2. DIMES, University of Calabria, Via Pietro Bucci Cube 44, 87036, Rende, CS, Italy

    Alessia Amelio

  3. Department of CS and IT, University of Lahore, 1-KM Defence Road, Lahore, Pakistan

    Nadeem Ahmad & Syed Khuram Shahzad

Authors
  1. Darko Brodić
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  2. Alessia Amelio
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  3. Nadeem Ahmad
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  4. Syed Khuram Shahzad
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Corresponding author

Correspondence to Darko Brodić .

Editor information

Editors and Affiliations

  1. Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    Somnuk Phon-Amnuaisuk

  2. Universiti Teknologi Brunei, Gadong, Brunei Darussalam

    Swee-Peng Ang

  3. Korea Advanced Institute of Science and Technology, Daejeon, Korea (Republic of)

    Soo-Young Lee

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Brodić, D., Amelio, A., Ahmad, N., Shahzad, S.K. (2017). Usability Analysis of the Image and Interactive CAPTCHA via Prediction of the Response Time. In: Phon-Amnuaisuk, S., Ang, SP., Lee, SY. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2017. Lecture Notes in Computer Science(), vol 10607. Springer, Cham. https://doi.org/10.1007/978-3-319-69456-6_21

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  • DOI: https://doi.org/10.1007/978-3-319-69456-6_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69455-9

  • Online ISBN: 978-3-319-69456-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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