Enhanced STE3D-CAP: A Novel 3D CAPTCHA Family

  • Yang-Wai Chow
  • Willy Susilo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7232)


With the growth of the Internet, its wide-ranging services are increasingly being threatened by adverse and malicious attacks. CAPTCHAs have emerged as a standard security countermeasure against Internet attacks such as distributed denial of service attacks and botnets. However, many CAPTCHA schemes themselves have been found to be susceptible to automated attacks. The task of designing a good CAPTCHA scheme is still an open and challenging question, as a good CAPTCHA must fulfil two fundamental requirements; namely, it must be secure against automated attacks whilst being human usable. This paper presents STE3D-CAP-e, a human usable text-based CAPTCHA that is robust against a variety of attacks. STE3D-CAP-e adopts a novel 3D CAPTCHA approach designed to capitalise on the inherent human ability to perceive depth from stereoscopic images. By presenting CAPTCHA challenges using stereoscopic images, humans can distinguish the main text from the background clutter in 3D. The various issues that were considered and addressed in the design of STE3D-CAP-e are described, along with a formal definition of its underlying AI problem family. This paper also presents analysis of STE3D-CAP-e in terms of its security and usability.


CAPTCHA stereoscopic usability segmentation-resistant 


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  1. 1.
    Baird, H.S., Moll, M.A., Wang, S.-Y.: A Highly Legible CAPTCHA That Resists Segmentation Attacks. In: Baird, H.S., Lopresti, D.P. (eds.) HIP 2005. LNCS, vol. 3517, pp. 27–41. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  2. 2.
    Birchfield, S., Tomasi, C.: Depth discontinuities by pixel-to-pixel stereo. International Journal of Computer Vision 35(3), 269–293 (1999)CrossRefGoogle Scholar
  3. 3.
    Bourke, P., Morse, P.: Stereoscopy: Theory and Practice. In: Workshop at the 13th International Conference on Virtual Systems and Multimedia, VSMM 2007 (2007),
  4. 4.
    Chellapilla, K., Larson, K., Simard, P.Y., Czerwinski, M.: Building Segmentation Based Human-Friendly Human Interaction Proofs (HIPs). In: Baird, H.S., Lopresti, D.P. (eds.) HIP 2005. LNCS, vol. 3517, pp. 1–26. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  5. 5.
    Elson, J., Douceur, J.R., Howell, J., Saul, J.: Asirra: a CAPTCHA that Exploits Interest-Aligned Manual Image Categorization. In: Ning, P., di Vimercati, S.D.C., Syverson, P.F. (eds.) ACM Conference on Computer and Communications Security, pp. 366–374. ACM (2007)Google Scholar
  6. 6.
    McAllister, D.: 3D Displays. Wiley Encyclopedia on Imaging, Pacific Grove, CA (2002)Google Scholar
  7. 7.
    Mitra, N.J., Chu, H.-K., Lee, T.-Y., Wolf, L., Yeshurun, H., Cohen-Or, D.: Emerging Images. ACM Trans. Graph. 28(5) (2009)Google Scholar
  8. 8.
    Mori, G., Malik, J.: Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA. In: CVPR (1), pp. 134–144 (2003)Google Scholar
  9. 9.
    Ross, S.A., Halderman, J.A., Finkelstein, A.: Sketcha: a CAPTCHA based on Line Drawings of 3D Models. In: Rappa, M., Jones, P., Freire, J., Chakrabarti, S. (eds.) WWW, pp. 821–830. ACM (2010)Google Scholar
  10. 10.
    Scharstein, D., Szeliski, R.: A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision 47(1-3), 7–42 (2002)zbMATHCrossRefGoogle Scholar
  11. 11.
    Susilo, W., Chow, Y.W., Zhou, H.: STE3D-CAP: Stereoscopic 3D CAPTCHA. In: Heng, S.-H., Wright, R.N., Goi, B.-M. (eds.) CANS 2010. LNCS, vol. 6467, pp. 221–240. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Tsin, Y., Kang, S.B., Szeliski, R.: Stereo matching with linear superposition of layers. IEEE Trans. Pattern Anal. Mach. Intell. 28(2), 290–301 (2006)CrossRefGoogle Scholar
  13. 13.
    von 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)CrossRefGoogle Scholar
  14. 14.
    Yan, J., Ahmad, A.S.E.: A Low-Cost Attack on a Microsoft CAPTCHA. In: Ning, P., Syverson, P.F., Jha, S. (eds.) ACM Conference on Computer and Communications Security, pp. 543–554. ACM (2008)Google Scholar
  15. 15.
    Yan, J., Ahmad, A.S.E.: Usability of CAPTCHAs or Usability Issues in CAPTCHA Design. In: Cranor, L.F. (ed.) SOUPS. ACM International Conference Proceeding Series, pp. 44–52. ACM (2008)Google Scholar
  16. 16.
    Yan, J., Ahmad, A.S.E.: CAPTCHA Security: A Case Study. IEEE Security & Privacy 7(4), 22–28 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yang-Wai Chow
    • 1
  • Willy Susilo
    • 2
  1. 1.Centre for Multimedia and Information ProcessingUniversity of WollongongAustralia
  2. 2.Centre for Computer and Information Security Research School of Computer Science and Software EngineeringUniversity of WollongongAustralia

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