Abstract
The Turing test plays an important role in discriminating humans from malicious automated programs and the Completely Automated Public Turing test to tell Computers and Humans Apart (CAPTCHA) has been widely used. A simple and very effective way to enhance CAPTCHA is to repeat the same kind of CAPTCHA tasks multiple times. However, the repetition of CAPTCHA tasks surely increases users’ psychological burden. This motivated us to study a new CAPTCHA configuration with the machine learning and brute-force attack defensibility without increasing users’ psychological burden. We propose “Directcha-maze” in which multiple CAPTCHA tasks are implicitly embedded in a maze. What users are conscious of is a maze solving task, and thus it is expected that users do not feel psychological burden on CAPTCHA tasks hidden in the maze; rather, solving a maze should be an enjoyable task for users. We developed a prototype Directcha-maze system and conducted a basic experiment. The results showed the effectiveness of our Directcha-maze system.
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Notes
- 1.
This is almost the same value as the five characters’ text-based CAPTCHA. A text-based CAPTCHA used by Google uses 5–7 lower-case alphabetic characters.
References
The Official CAPTCHA Site. http://www.captcha.net/
Elson, J., Douceur, J., Howela, J., Saul, J.: Asirra: a CAPTCHA that exploit interest aligned manual image categorization. In: 2007 ACM CSS, pp. 366–374 (2007)
Yan, J., Ahmad, A.S.E.: Breaking visual CAPTCHAs with naïve pattern recognition algorithms. In: 2007 Computer Security Applications Conference, pp. 279–291 (2007)
Golle, P.: Machine learning attacks against the ASIRRA CAPTCHA. In: 2008 ACM CSS, pp. 535–542 (2008)
Yamamoto, T., Tygar, J.D., Nishigaki, M.: CAPTCHA using strangeness in machine translation. In: The 24th International Conference on Advanced Information Networking and Applications, pp. 430–437 (2010)
Ross, S., Halderman, J., Finkelstein, A.: Sketcha: a Captcha based on line drawings of 3D models. In: The 19th International Conference on World Wide Web, pp. 821–830 (2010)
Sano, A., Fujita, M., Nishigaki, M.: Directcha: A Proposal of Spatiometric Mental Rotation CAPTCHA. In: The 14th International Conference on Privacy, Security and Trust, pp. 585–592 (2016)
Fujita, M., Ikeya, Y., Kani, J., Nishigaki, M.: Chimera CAPTCHA: a proposal of CAPTCHA using strangeness in merged objects. In: The 17th International Conference on Human-Computer Interaction, pp. 48–58 (2015)
Fujita, M., Ikeya, Y., Kani, J., Nishigaki, M.: An unrealistic image CAPTCHA: A 3DCG CAPTCHA using something different from common sense. IPSJ J. 56(12), 2324–2336 (2015). (in Japanese)
Shepard, R., Cooper, L.: Mental Images and Their Transformations. MIT Press, Cambridge (1982)
Shepard, R., Metzler, J.: Mental rotation of three dimensional objects. Sci. New Ser. 171(3972), 701–703 (1971)
Acknowledgements
In this study, we used free 3D models published on Metaseko-Sozai (http://sakura.hippy.jp/meta/) and TurboSquid (http://www.turbosquid.com/). We would like to thank Prof. Yugo Takeuchi of Shizuoka University for his valuable advice regarding to cognitive science. We also would like to thank Mr. Hiroaki Matsuno of Shizuoka University for his support regarding to a part of the implementation of Directcha-maze system.
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Sano, A., Fujita, M., Nishigaki, M. (2018). Directcha-maze: A Study of CAPTCHA Configuration with Machine Learning and Brute-Force Attack Defensibility Along with User Convenience Consideration. In: Barolli, L., Xhafa, F., Conesa, J. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 12. Springer, Cham. https://doi.org/10.1007/978-3-319-69811-3_45
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DOI: https://doi.org/10.1007/978-3-319-69811-3_45
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