Skip to main content

Advertisement

SpringerLink
Log in

An investigation of the usability of image-based CAPTCHAs using PROMETHEE-GAIA method

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Today, it is difficult to find an adequate Web site with a registration form that is not protected with some automated human proof test. One of the oldest concepts in Artificial Intelligence as a security mechanism based on the Turing Test is CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart). This test was designed to make a difference between the real users and bots and provide security against malicious attacks. The PROMETHEE-GAIA method was employed for ranking different image-based CAPTCHAs according to their usability in this paper. The aim of this study is a comparative analysis of seven image-based CAPTCHAs based on three different criteria: time to find a solution, a number of attempts, and task difficulty. The weights of the considered criteria were calculated objectively by the entropy method, and for the subjective weights, Analytical Hierarchy Process (AHP) was used. A defined research model was applied through four phases. The survey included 320 randomly selected Internet users and experts in computer science who were familiar with CAPTCHA tests. The proposed model suggested which CAPTCHA offered better human accuracy and lower machine attack rates compared to the existing approaches. The obtained results were very helpful to the web administrators because they indicated that this approach could provide useful insights for the decision-makers about the appropriate mechanisms to protect users against cyber-criminal activities and Internet threats.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Abdel-Basset M (2019) A neutrosophic theory-based security approach for fog and mobile-edge computing. Comput Netw 157:122–132

    Article  Google Scholar 

  2. Abdullah L, Chan W, Afshari A (2019) Application of PROMETHEE method for green supplier selection: a comparative result based on preference functions. J Ind Eng Int 15(2):271–285

    Article  Google Scholar 

  3. Agha SR, Nofal LG, Nassar HA (2012) Multi-criteria governmental crop planning problem based on an integrated AHP-PROMETHEE approach. Int J Appl Manag Sci 4(4):385–406

    Article  Google Scholar 

  4. Aherwar A, Singh T, Singh A, Patnaik A, Fekete G (2019) Optimum selection of novel developed implant material using hybrid entropy-PROMETHEE approach. Mater Werkst 50(10):1232–1241

    Article  Google Scholar 

  5. Alqahtani FH, Alsulaiman FA (2020) Is image-based CAPTCHA secure against attacks based on machine learning? An experimental study. Comput Secur 88:101635

    Article  Google Scholar 

  6. Beheshti SMRS, Liatsis P, Rajarajan M (2017) A CAPTCHA model based on visual psychophysics: using the brain to distinguish between human users and automated computer bots. Comput Secur 70:596–617

    Article  Google Scholar 

  7. Behzadian M, Kazemzadeh RB, Albadvi A, Aghdasi M (2010) PROMETHEE: a comprehensive literature review on methodologies and applications. Eur J Oper Res 200(1):198–215

    Article  Google Scholar 

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

    Article  Google Scholar 

  9. Ben-Abdallah E, Boukadi K, Lloret J, Hammami M (2019) CROSA: context-aware cloud service ranking approach using online reviews based on sentiment analysis. Concurr Comput 1–16

  10. Bennani A, Bahi L, Amgaad S (2017) Using a combined approach AHP PROMETHEE to make a decision about roads alternative project: a case study. Int J Civ Eng Technol 8(5):856–868

    Google Scholar 

  11. Brans J, Mareschal B (2005) PROMETHEE methods. Multiple Criteria Decision Analysis: State of the Art Surveys, pp 163–186

  12. Brans JP (1982) Lingenierie de la decision, elaboration dinstruments daide a la decision. Methode PROMETHEE. In: Nadeau R, Landry M (eds) Laide a la decision: nature, instruments et perspectives Davenir. Presses de Universite Laval, Quebec, pp 183–214

    Google Scholar 

  13. Brans JP, Mareschal B, Vincke PH (1984) PROMETHEE: a new family of outranking methods in multi-criteria analysis. In: Brans JP (ed) Operational research ‘84. North-Holland, Amsterdam, pp 477–490

    Google Scholar 

  14. Bursztein, E, Moscicki, A, Fabry, C, Bethard, S, Mitchell, JC, Jurafsky, D. (2014). Easy does it: more usable captchas. In: Proceedings of the 32nd Annual ACM Conference on Human Factors in Computing Systems, ACM, pp 2637–46

  15. Bursztein E, Bethard S, Fabry C, Mitchell J, Jurafsky D (2010) How good are humans at solving captchas? A large scale evaluation. In: 2010 IEEE symposium on security and privacy, pp 399–413

  16. Chandavale AA, Sapkal AM (2015) Systematic approach to measure strength of textbased CAPTCHA. In: 2015 International Conference on Information Processing (ICIP), pp 382–387

  17. Cheriet M, Bunke H, Hu J, Kimura F, Suen CY (2009) New Frontiers in handwriting recognition. Pattern Recogn 42(12):3129–3130

    Article  Google Scholar 

  18. Christian AV, Zhang Y, Salifou C (2016) Application of PROMETHEE-GAIA method in the entry mode selection process in international market expansion. Open J Bus Manag 4:238–250

    Article  Google Scholar 

  19. D’Avignon G, Turcotte M, Beaudry L, Duperre Y (1983) Degrt de specialisation des hopitaux de Quebec. Technical report. Universite Laval, Quebec

    Google Scholar 

  20. Dujardin M (1984) Une evaluation multicritere de projets de remediation a l'echec dans I' enseignement secondaire Belge. In XIX Meeting of the European Working Group on Multiple Criteria Decision Aid, Liege, France

  21. Fidas CA, Voyiatzis AG, Avouris NM (2011) On the necessity of user-friendly CAPTCHA. In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM, pp 2623–2626

  22. Goswami G, Singh R, Vatsa M, Powell B, Noore A (2012) Face recognition captcha. In: Proceedings of the Fifth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), IEEE, pp 412–17

  23. Herngren L, Goonetilleke A, Ayoko GA (2006) Analysis of heavy metals in roaddeposited sediments. Anal Chim Acta 571(2):270–278

    Article  Google Scholar 

  24. Hidalgo JMG, Alvarez G (2011) Chapter 3 - CAPTCHAs: an artificial intelligence application to web security. Adv Comput 83:109–181

    Article  Google Scholar 

  25. Karpathy A, Fei-Fei L (2015) Deep visual-semantic alignments for generating image descriptions. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp 3128–3137

  26. Keller HR, Massart DL, Brans JP (1991) Multicriteria decision making: a case study. Chemom Intell Lab Syst 11:175–189

    Article  Google Scholar 

  27. Kluever KA (2008) Evaluating the usability and security of a video CAPTCHA. Rochester Institute of Technology. Thesis. Rochester Institute of Technology. Accessed from https://scholarworks.rit.edu/theses/163

  28. Kluever KA, Zanibbi R (2009) Balancing usability and security in a video CAPTCHA. In: Proceedings of the 5th Symposium on Usable Privacy and Security, ACM, pp 11–14

  29. Kocmanova A, Docekalova M, Lunacek J (2013) PROMETHEE-GAIA method as a support of the decision-making process in evaluating technical facilities. IFIP Adv Inf Commun Technol 413:44–53

    Article  Google Scholar 

  30. Kwon S, Cha S (2017) CAPTCHA-based image annotation. Inf Process Lett 128:27–31

    Article  MathSciNet  Google Scholar 

  31. Lee YL, Hsu CH (2011) Usability study of text-based CAPTCHAs. Displays 32(2):81–86

    Article  Google Scholar 

  32. Lopes APF, Muñoz MM, Alarcón-Urbistondo P (2018) Regional tourism competitiveness using the PROMETHEE approach. Ann Tour Res 73:1–13

    Article  Google Scholar 

  33. Macharis C, Springael J, De Brucker K, Verbeke A (2004) PROMETHEE and AHP: the design of operational synergies in multicriteria analysis. Strengthening PROMETHEE with ideas of AHP. Eur J Oper Res 153:307–317

    Article  Google Scholar 

  34. Madathil KC, Alapatt GF, Greenstein JS (2010) An investigation of the usability of image-based CAPTCHAs. Proc Hum Factors Ergon Soc Ann Meet 54(16):1249–1253

    Article  Google Scholar 

  35. Madathil KC, Greenstein JS, Horan K (2019) Empirical studies to investigate the usability of text-and image-based CAPTCHAs. Int J Ind Ergon 69:200–208

    Article  Google Scholar 

  36. Meutzner H, Nguyen V-H, Holz T, Kolossa D (2014) Using automatic speech recognition for attacking acoustic captchas: the tradeoff between usability and security. In: Proceedings of the 30th Annual Computer Security Applications Conference, ACM, pp 276–85

  37. Nikolić D, Jovanović I, Mihajlović I, Živković Ž (2009) Multi-criteria ranking of copper concentrates according to their quality – an element of environmental management in the vicinity of copper – smelting complex in Bor, Serbia. J Environ Manag 91:509–515

    Article  Google Scholar 

  38. Ostovare M, Shahraki MR (2019) Evaluation of hotel websites using the multicriteria analysis of PROMETHEE and GAIA: evidence from the five-star hotels of Mashhad. Tour Manag Perspect 30:107–116

    Article  Google Scholar 

  39. Pashalidis A, Mavrogiannopoulos N, Ferrer X, Bermejo Olaizola B (2012) For human eyes only: security and usability evaluation. In: Proceedings of the 2012 ACM Workshop on Privacy in the Electronic Society, ACM, pp 129–40

  40. Penninger S, Meier S, Federrath H (2012) Usability von CAPTCHA-Systemen. In: GI Sicherheit, Darmstadt, 195:199–208

  41. Plamondon R, Pirlo G, Anquetil É, Rémi C, Teulings H-L, Nakagawa M (2018) Personal digital bodyguards for e-security, e-learning and e-health: a prospective survey. Pattern Recogn 81:633–659

    Article  Google Scholar 

  42. Radulescu M, Fedajev A, Nikolic D (2017) Ranking of EU national banking systems using multi-criteria analysis in the light of BREXIT. Acta Oeconomica 67(4):473–509

    Article  Google Scholar 

  43. Roshanbin N, Miller J (2016) ADAMAS: interweaving unicode and color to enhance CAPTCHA security. Futur Gener Comput Syst 55:289–310

    Article  Google Scholar 

  44. Saaty TL (1980) The analytic Hieararchy process. McGraw-Hill, New York

    Google Scholar 

  45. Sauer G, Hochheiser H (2008) Towards a universally usable CAPTCHA. In: Proceedings of the 4th symposium on usable privacy and security, pp 2–5

  46. Savic M, Nikolic D, Mihajlovic I, Zivkovic Z, Bojanov B, Djordjevic P (2015) Multi-criteria decision support system for optimal blending process in zinc production. Mineral Process Ext Metall Rev Int J 36(4):267–280

    Article  Google Scholar 

  47. Schryen G, Wagner G, Schlegel A (2016) Development of two novel face-recognition CAPTCHAs: a security and usability study. Comput Secur 60:95–116

    Article  Google Scholar 

  48. Shirali-Shahreza S, Penn G, Balakrishnan R, Ganjali Y (2013) Seesay and hearsay captcha for mobile interaction. In: Proceedings of the SIGCHI conference on human factors in computing systems, ACM, pp 2147–56

  49. Starostenko O, Cruz-Perez C, Uceda-Ponga F, Alarcon-Aquino V (2015) Breaking text-based CAPTCHAs with variable word and character orientation. Pattern Recogn 48(4):1101–1112

    Article  Google Scholar 

  50. Thomas AO, Rusu A, Govindaraju V (2009) Synthetic handwritten CAPTCHAs. Pattern Recogn 42(12):3365–3373

    Article  Google Scholar 

  51. Trukenbrod AK, Backhaus N, Thomaschke R (2020) Measuring subjectively experienced time in usability and user experience testing scenarios. Int J Hum Comput Stud 138:102399

    Article  Google Scholar 

  52. Vego G, Kučar-Dragičević S, Koprivanac N (2008) Application of multi-criteria decision-making on strategic municipal solid waste management in Dalmatia, Croatia. Waste Manag 28:2192–2201

    Article  Google Scholar 

  53. Vikram S, Fan Y, Gu G (2011) Semage: a new image-based two-factor CAPTCHA. In: Proceedings of the 27th Annual Computer Security Applications Conference, ACM, pp 237–246

  54. von Ahn LV, Blum M, Hopper NJ, Langford J (2003) CAPTCHA: Using hard AI problems for security. EUROCRYPT'03: Proceedings of the 22nd international conference on theory and applications of cryptographic techniques, pp 294–311. Accessed 13 Jan 2020

  55. Wang JJ, Wei CM, Yang D (2006) Decision method for vendor selection based on AHP/PROMETHEE/GAIA. J Dalian Univ Technol 46(6):926–931

    Google Scholar 

  56. Yan J, El Ahmad AS (2008a) Usability of CAPTCHAs or usability issues in CAPTCHA design. Symposium on usable privacy and security, Pittsburgh

  57. Yan J, El Ahmad AS (2008b) Usability of CAPTCHAs or usability issues in CAPTCHA design. In: Proceedings of the 4th Symposium on Usable Privacy and Security, Pittsburgh, Pennsylvania, USA, pp 44–52

  58. Yu X, Xu Z, Ma Y (2013) Prioritized multi-criteria decision making based on the idea of PROMETHEE. Proc Comput Sci 17:449–456

    Article  Google Scholar 

  59. Zhi-Hong Z, Yi Y, Jing-nan S (2006) Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment. J Environ Sci 18:1020–1023

    Article  Google Scholar 

  60. Zindani D, Kumar K (2018) Material selection for turbine seal strips using PROMETHEE-GAIA method. Materials Today: Proceedings 5:17533–17539

Download references

Acknowledgments

Responsible for the English language in the paper is Sandra Vasković, the English language teacher.

Author information

Authors and Affiliations

  1. Engineering Management Department, Technical Faculty in Bor, University of Belgrade, Bor, 19210, Serbia

    Sanela Arsić, Djordje Nikolic & Milena Jevtic

Authors
  1. Sanela Arsić
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Djordje Nikolic
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Milena Jevtic
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sanela Arsić.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Arsić, S., Nikolic, D. & Jevtic, M. An investigation of the usability of image-based CAPTCHAs using PROMETHEE-GAIA method. Multimed Tools Appl 80, 9393–9409 (2021). https://doi.org/10.1007/s11042-020-10054-w

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-020-10054-w

Keywords

Search

Navigation