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Eye Gaze and Interaction Differences of Holistic Versus Analytic Users in Image-Recognition Human Interaction Proof Schemes

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HCI for Cybersecurity, Privacy and Trust (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12788))

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Abstract

Image-recognition Human Interaction Proof (HIP) schemes are widely used security defense mechanisms that are utilized by service providers to determine whether a human user is interacting with their system and not malicious software. Inspired by recent research, which underpins the necessity for designing user-centered HIPs, this paper examines, in the frame of an accredited cognitive style theory (Field Dependence-Independence – FD-I), whether human cognitive differences in visual information processing affect users’ visual behavior when interacting with an image-recognition HIP challenge. For doing so, we conducted an eye tracking study (n = 46) in which users solved an image-recognition HIP challenge. Analysis of users’ interactions and eye gaze data revealed differences in users’ visual behavior and interactions between Holistic and Analytic users within image-recognition HIP tasks. Findings underpin the added value of considering users’ cognitive processing differences in the design of adaptive and adaptable HIP security schemes.

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References

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

    Article  Google Scholar 

  2. Chellapilla, K., Larson, K., Simard, P., Czerwinski, M., 2005. Designing human friendly human interaction proofs (HIPs). In: ACM CHI 2005, pp. 711–720. ACM (2005)

    Google Scholar 

  3. Golle, P.: Machine learning attacks against the Asirra CAPTCHA. In: ACM Conference on Computer and Communications Security (CCS 2008), pp. 535–542. ACM (2008)

    Google Scholar 

  4. Bursztein, E., Martin, M., Mitchell, J.: Text-based CAPTCHA strengths and weaknesses. In: ACM Computer and Communications Security (CCS 2011), pp. 125–138. ACM (2011)

    Google Scholar 

  5. Belk, M., Fidas, C., Germanakos, P., Samaras, G.: Do human cognitive differences in information processing affect preference and performance of captcha? J. Hum.-Comput. Stud. 84, 1–18 (2015)

    Google Scholar 

  6. reCAPTCHA. Online: https://www.google.com/recaptcha/about

  7. Constantinides, A., Pietron, A., Belk, M., Fidas, C., Han, T., Pitsillides, A.: A cross-cultural perspective for personalizing picture passwords. In: ACM User Modeling, Adaptation and Personalization (UMAP 2020), pp. 43–52. ACM (2020)

    Google Scholar 

  8. Constantinides, A., Fidas, C., Belk, M., Pietron, A.M., Han, T., Pitsillides, A.: From hot-spots towards experience-spots: leveraging on users’ sociocultural experiences to enhance security in cued-recall graphical authentication. Int. J. Hum.-Comput. Stud., 149 (2021). https://doi.org/10.1016/j.ijhcs.2021.102602

  9. Davidoff, J., Fonteneau, E., Fagot, J.: Local and global processing: observations from a remote culture. Cognition 108(3), 702–709 (2008)

    Article  Google Scholar 

  10. Witkin, H.A., Moore, C.A., Goodenough, D.R., Cox, P.W.: Field–dependent and field–independent cognitive styles and their educational implications. ETS Res. Bull. Series 2, 1–64 (1975)

    Article  Google Scholar 

  11. Belk, M., Fidas, C., Katsini, C., Avouris, N., Samaras, G.: Effects of human cognitive differences on interaction and visual behavior in graphical user authentication. In: Bernhaupt, R., Dalvi, G., Joshi, A., K. Balkrishan, D., O’Neill, J., Winckler, M. (eds.) INTERACT 2017. LNCS, vol. 10515, pp. 287–296. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-67687-6_19

    Chapter  Google Scholar 

  12. Hong, J., Hwang, M., Tam, K., Lai, Y., Liu, L.: Effects of cognitive style on digital jigsaw puzzle performance: a GridWare analysis. Comput. Hum. Behav. 28(3), 920–928 (2012)

    Article  Google Scholar 

  13. Rittschof, K.A.: Field dependence-independence as visuospatial and executive functioning in working memory: implications for instructional systems design and research. Educ. Technol. Res. Dev. 58(1), 99–114 (2010)

    Article  Google Scholar 

  14. Angeli, C., Valanides, N., Kirschner, P.: Field dependence-independence and instructional-design effects on learners’ performance with a computer-modeling tool. Comput. Hum. Behav. 25(6), 1355–1366 (2009)

    Article  Google Scholar 

  15. Belk, M., Fidas, C., Germanakos, P., Samaras, G.: The interplay between humans, technology and user authentication: a cognitive processing perspective. Comput. Hum. Behav. 76, 184–200 (2017)

    Article  Google Scholar 

  16. GP3 Eye Tracker. Online. https://www.gazept.com

  17. Constantinides, A., Belk, M., Fidas, C., Pitsillides, A.: On the accuracy of eye gaze-driven classifiers for predicting image content familiarity in graphical passwords. In: ACM UMAP 2019, pp. 201–205. ACM (2019)

    Google Scholar 

  18. Witkin, H.A., Oltman, P., Raskin, E., Karp, S.: A Manual for the Embedded Figures Test. Consulting Psychologists Press, Palo Alto, CA (1971)

    Google Scholar 

  19. Alt, F., Schneegass, S., Shirazi, A.S., Hassib, M., Bulling, A.: Graphical passwords in the wild: understanding how users choose pictures and passwords in image-based authentication schemes. In: ACM MobileHCI 2015, pp. 316–322 (2015)

    Google Scholar 

  20. Dunphy, P., Yan, J.: Do background images improve draw a secret graphical passwords? In: ACM Computer and Communications Security, pp. 36–47. ACM (2007)

    Google Scholar 

  21. Zhao, Z., Ahn, G., Hu, H.: Picture Gesture Authentication: Empirical Analysis, Automated Attacks, and Scheme Evaluation. Journal of ACM Transactions on Information and System Security (TISSEC) 17, 4, Article 14, 37 pages (2015)

    Google Scholar 

  22. Wiedenbeck, S., Waters, J., Birget, J.C., Brodskiy, A., Memon, N.: Authentication using graphical passwords: Effects of tolerance and image choice. In: ACM Symposium on Usable privacy and security, pp. 1–12. ACM (2005)

    Google Scholar 

  23. Katsini, C., Fidas, C., Raptis, G. E., Belk, M., Samaras, G., Avouris, N.: Influences of human cognition and visual behavior on password strength during picture password composition. In: CHI 2018, p. 87. ACM (2018)

    Google Scholar 

  24. Fidas, C., Voyiatzis, A., Avouris, N.: On the necessity of user-friendly CAPTCHA. In: ACM CHI 2011, pp. 2623–2626. ACM (2011)

    Google Scholar 

  25. Belk, M., Germanakos, P., Fidas, C., Holzinger, A., Samaras, G.: Towards the personalization of CAPTCHA mechanisms based on individual differences in cognitive processing. Springer Human Factors in Computing and Informatics (SouthCHI 2013), Springer-Verlag, pp. 409–426 (2013)

    Google Scholar 

  26. Belk, M., Fidas, C., Germanakos, P., Samaras, G.: Do cognitive styles of users affect preference and performance related to CAPTCHA challenges? In: CHI 2012 Extended Abstracts on Human Factors in Computing Systems (CHI EA 2012), pp. 1487–1492. ACM (2012)

    Google Scholar 

  27. Elson, J., Douceur, J., Howell, J., Saul, J.: Asirra: a CAPTCHA that Exploits interest-aligned manual image categorization. In: Proceedings of the International Conference on Computer and Communications Security (CCS 2007), pp. 366–374. ACM (2007)

    Google Scholar 

  28. Belk, M., Germanakos, P., Fidas, C., Spanoudis, G., Samaras, G.: Studying the Effect of Human Cognition on Text and Image Recognition CAPTCHA Mechanisms. HCI 27, 71–79 (2013)

    Google Scholar 

  29. Vikram, S., Fan, Y., Gu, G.: SEMAGE: a new image-based two-factor CAPTCHA. In: ACM Conference on Computer Security Applications (CCS 2011), pp. 237–246. ACM (2011)

    Google Scholar 

  30. Fidas, C., Hussmann, H., Belk, M., Samaras, G.: IHIP: towards a user centric individual human interaction proof framework. In: CHI ‘15 Extended Abstracts on Human Factors in Computing Systems (CHI EA ‘15), pp. 2235–2240. ACM (2015)

    Google Scholar 

  31. Gossweiler, R., Kamvar, M., Baluja, S.: What’s up CAPTCHA?: a CAPTCHA based on image orientation. In: ACM World Wide Web (WWW 2009), pp. 841–850. ACM (2009)

    Google Scholar 

  32. Tanthavech, N., Nimkoompai, A.: CAPTCHA: Impact of website security on user experience. In: Proceedings of the 2019 4th International Conference on Intelligent Information Technology (ICIIT 2019), pp. 37–41. ACM (2019)

    Google Scholar 

  33. Sim, T., Nejati, H., Chua, J.: Face recognition CAPTCHA made difficult. In: Proceedings of the 23rd International Conference on World Wide Web (WWW 2014 Companion), pp. 379–380. ACM (2014)

    Google Scholar 

  34. Shishkin, A., Bezzubtseva, A., Fedorova, V., Drutsa, A., Gusev, G.: Text recognition using anonymous CAPTCHA answers. In: ACM Web Search and Data Mining (WSDM 2020), pp. 537–545. ACM (2020)

    Google Scholar 

  35. Lazar, J., et al.: The SoundsRight CAPTCHA: an improved approach to audio human interaction proofs for blind users. In: ACM Conference on Human Factors in Computing Systems (CHI 2012), pp. 2267–2276. ACM (2012)

    Google Scholar 

  36. Jiang, N., Tian, F.: A novel gesture-based CAPTCHA design for smart devices. In: BCS Human Computer Interaction Conference (BCS-HCI ‘13). BCS Learning & Development Ltd., Swindon, GBR, Article 49, pp. 1–5 (2013)

    Google Scholar 

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Acknowledgements

This research has been partially funded by the EU Horizon 2020 Grant 826278 “Securing Medical Data in Smart Patient-Centric Healthcare Systems” (Serums), and the Research and Innovation Foundation (Project DiversePass: COMPLEMENTARY/0916/0182).

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Authors and Affiliations

  1. University of Cyprus, Nicosia, Cyprus

    Pantelitsa Leonidou, Argyris Constantinides, Marios Belk & Andreas Pitsillides

  2. Cognitive UX Ltd., Nicosia, Cyprus

    Argyris Constantinides

  3. Cognitive UX GmbH, Heidelberg, Germany

    Marios Belk

  4. University of Patras, Patras, Greece

    Christos Fidas

Authors
  1. Pantelitsa Leonidou
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  2. Argyris Constantinides
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  3. Marios Belk
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  4. Christos Fidas
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  5. Andreas Pitsillides
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Corresponding author

Correspondence to Marios Belk .

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Editors and Affiliations

  1. San Jose State University, San Jose, CA, USA

    Abbas Moallem

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Leonidou, P., Constantinides, A., Belk, M., Fidas, C., Pitsillides, A. (2021). Eye Gaze and Interaction Differences of Holistic Versus Analytic Users in Image-Recognition Human Interaction Proof Schemes. In: Moallem, A. (eds) HCI for Cybersecurity, Privacy and Trust. HCII 2021. Lecture Notes in Computer Science(), vol 12788. Springer, Cham. https://doi.org/10.1007/978-3-030-77392-2_5

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  • DOI: https://doi.org/10.1007/978-3-030-77392-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77391-5

  • Online ISBN: 978-3-030-77392-2

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