The Design and Evaluation of Novel Ananimated CAPTCHA Schemes Based on Humans’ Natural Vision Capabilities

Authors

  • Rafaqat Hussain Arain Institute of Computer Science,Shah Abdul Latif University, Khairpur, Sindh
  • Riaz Ahmed Shaikh Institute of Computer Science,Shah Abdul Latif University, Khairpur, Sindh, Paskitan
  • Safdar Ali Shah Institute of Computer Science,Shah Abdul Latif University, Khairpur, Sindh, Paskitan
  • Sajjad Ali Shah Institute of Computer Science,Shah Abdul Latif University, Khairpur, Sindh, Paskitan
  • Saima Rafique Government Girls Degree College, Pir Jo Goth, Sindh, Pakistan

DOI:

https://doi.org/10.21015/vtse.v11i2.1547

Abstract

CAPTCHAs are ubiquitously found on the web these days. It is most commonly used security mechanism against bots. Numerous design variants of static text-based CAPTCHAs were proposed and implemented on the internet over the years. However due to advancements in machine learning and image processing techniques they were proved vulnerable against automated attacks. In this research a new and robust animated CAPTCHA scheme is presented which is based on human’s natural vision capabilities. The newly designed CAPTCHAs are user friendly for humans but extremely hard for bots. The security and usability is kept in mind while designing these CAPTCHAs. Various types of characters, patterns and filters are used to protect them against automated attacks. Overall, 20 types of animated CAPTCHAs are designed in this work. Further in this research, a group of participants have evaluated the usability of newly designed CAPTCHAs and solved with an average success rate of 76.85%. The analysis has proved that the proposed scheme is very much usable for humans and extremely difficult for bots.

References

L. V. Ahn, M. Blum and J. Langford, “Telling humans and computers apart automatically, ” Communications of the ACM. ACM New York. NY USA 47(2) pp. 56–60, 2004. https://doi.org/10.1145/966389.966390 DOI: https://doi.org/10.1145/966389.966390

Y. Chow, W. Susilo and P. Thorncharoensri, “CAPTCHA design and security issues,” Advances in Cyber Security: Principles, Techniques, and Applications. Springer, pp. 69–92, 2019. https://doi.org/10.1007/978-981-13-1483-4_4

Creo.Group. (2012) HelloCAPTCHA vs Spambots. Available at: http://www.hellocaptcha.com (Accessed: 26 January 2023).

S.S. A. Shah, R. A. Shaikh and R. H. Arain, “Reading the Moving Text in Animated Text-Based CAPTCHAs,” International Journal of Advanced Computer Science and Applications, Vol. 9, No. 12, 2018. https://doi.org/10.14569/IJACSA.2018.091209

A.M. Turing, “Computing Machinery and Intelligence,” Mind 59 (236), 433-460, (1950).https://doi.org/10.1093/mind/LIX.236.433 DOI: https://doi.org/10.1093/mind/LIX.236.433

H,S. Baird, A.L. Coates and R.J Fateman, “Pessimalprint: a reverse turing test,” International Journal on Document Analysis and Recognition, Springer, 5(2–3), pp. 158–163, 2003.https://doi.org/10.1109/ICDAR.2001.953966 DOI: https://doi.org/10.1007/s10032-002-0089-1

J. Yan, “Bot, cyborg and automated turing test,” International Workshop on Security Protocols. Springer, pp. 190–197, 2006. https://doi.org/10.1007/978-3-642-04904-0_26 DOI: https://doi.org/10.1007/978-3-642-04904-0_26

J. Yan and A.S. El Ahmad, “A Low-cost Attack on a Microsoft CAPTCHA,” Proceedings of the 15th ACM conference on Computer and communications security, pp. 543–554, 2008. https://doi.org/10.1145/1455770.1455839 DOI: https://doi.org/10.1145/1455770.1455839

Y. W. Chow and W. Susilo, “AniCAP: An animated 3D CAPTCHA scheme based on motion parallax,” International Conference on Cryptology and Network Security. Springer, pp. 255–271, 2011. https://doi.org/10.1007/978-3-642-25513-7_18 DOI: https://doi.org/10.1007/978-3-642-25513-7_18

V.D. Nguyen, Y.W. Chow and W. Susilo, “Attacking animated CAPTCHAs via character extraction,” International Conference on Cryptology and Network Security. Springer, pp. 98–113, 2012. https://doi.org/10.1007/978-3-642-35404-5_9 DOI: https://doi.org/10.1007/978-3-642-35404-5_9

K. Kunitani and R. Uda, “Proposal of CAPTCHA using three dimensional objects,” Proceedings of the 7th International Conference on Ubiquitous Information Management and Communication, pp. 1–6, 2013. https://doi.org/10.1145/2448556.2448613 DOI: https://doi.org/10.1145/2448556.2448613

L.M.T. Inc. (2013) NuCAPTCHA. Available at: http://www.nucaptcha.com

V.D Nguyen, Y.W. Chow, and W. Susilo, “Breaking an animated CAPTCHA scheme,” Applied Cryptography and Network Security: 10th International Conference, ACNS 2012, Singapore, June 26-29, 2012. Proceedings 10 (pp. 12-29). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-31284-7_2 DOI: https://doi.org/10.1007/978-3-642-31284-7_2

Y. Raut, S. Pote, H. Boricha and P. Gunjgur A Robust Captcha Scheme for Web Security. 6th International Conference On Computing, Communication, Control And Automation, ICCUBEA, pp. 1-6, 2022. IEEE. 10.1109/ICCUBEA54992.2022.10011113

M. Kumar, M.K. Jindal and M. Kumar, “A systematic survey on CAPTCHA recognition: types, creation and breaking techniques,” Archives of Computational Methods in Engineering, 29(2), 1107-1136, 2022. https://doi.org/10.1007/s11831-021-09608-4

R. Hussain, H. Gao and R.A. Shaikh, “Segmentation of connected characters in text-based CAPTCHAs for intelligent character recognition,” Multimedia Tools and Applications. Springer, 76(24), pp. 25547–25561, 2017. https://doi.org/10.1007/s11042-016-4151-2 DOI: https://doi.org/10.1007/s11042-016-4151-2

R.H. Arain, R.A. Shaikh, K. Kumar, A. Maitlo, A. Kehar, S.A Shah and H. Shiakh, “Verifying the Robustness of Textbased CAPTCHAs offered by Local E-Commerce Sites,” Int. J. Comput. Sci. Netw. Secur, 18(9), 79-84, 2018.

J. Nian, P. Wang, H. Gao and X. Guo, “A deep learning based attack on text CAPTCHAs by using object detection techniques,” IET Information Security, 16(2), 97-110, 2022. https://doi.org/10.1049/ise2.12047

N.T. Dinh and V.T. Hoang, “Recent advances of Captcha security analysis: a short literature review,” Procedia Computer Science, 218, 2550-2562, 2023.

https://doi.org/10.1016/j.procs.2023.01.229

S. A. Sheikh and M.T Banday, “A Novel Animated CAPTCHA Technique based on Persistence of Vision,” International Journal of Advanced Computer Science and Applications, 13(2), 2022.

https://doi.org/10.14569/IJACSA.2022.0130242

M. Kumar, M.K. Jindal and M. Kumar, “A systematic survey on CAPTCHA recognition: types, creation and breaking techniques,” Archives of Computational Methods in Engineering, 29(2), 1107-1136, 2022.

https://doi.org/10.1007/s11831-021-09608-4

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Published

2023-06-30

How to Cite

Arain, R. H., Shaikh, R. A., Shah, S. A., Shah, S. A., & Rafique, S. (2023). The Design and Evaluation of Novel Ananimated CAPTCHA Schemes Based on Humans’ Natural Vision Capabilities. VFAST Transactions on Software Engineering, 11(2), 196–214. https://doi.org/10.21015/vtse.v11i2.1547

Issue

Vol. 11 No. 2 (2023): April-June

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