Abstract
Current CAPTCHAs require users to solve objective questions such as text recognition or image recognition. We propose a class of CAPTCHAs based on collaborative filtering. Collaborative filtering CAPTCHAs allow us to ask questions that have no absolute answer; instead, the CAPTCHAs are graded by comparison to other people’s answers. We analyze the security requirements of collaborative filtering CAPTCHAs and find that although they are not ready to use now, collaborative filtering CAPTCHAs are worthy of further investigation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Berman, J., Bruckman, A.S.: The Turing game: Exploring identity in an online environment. Convergence 7(3), 83–102 (2001)
Blum, M., von Ahn, L.A., Langford, J., Hopper, N.: The CAPTCHA Project, http://www.captcha.net (November 2000)
Breese, J., Heckerman, D., Kadie, C.: Empirical analysis of predictive algorithms for collaborative filtering. In: Fourteenth Conference on Uncertainty in Artificial Intelligence (1998)
Chew, M., Tygar, J.D.: Image recognition CAPTCHAs. In: 7th Annual Information Security Conference, August 2004, pp. 268–279 (2004)
Dellarocas, C.: Immunizing online reputation reporting systems against unfair ratings and discriminatory behavior. In: 2nd ACM Conference on Electronic Commerce (2000)
Goldberg, K., Hennessy, R., Gupta, D., Perkins, C., Narita, H., DiGiovanni, M.: Jester, http://shadow.ieor.berkeley.edu/humor (1999)
Goldberg, K., Roeder, T., Gupta, D., Perkins, C.: Eigentaste: A constant time collaborative filtering algorithm. Information Retrieval 4(2), 133–151 (2001)
Mendenhall, W., Sincich, T.: Statistics for Engineering and the Sciences, 3rd edn. Dellen Publishing Company. (1992)
Miller, B., Albert, I., Lam, S.K., Konstan, J., Riedl, J.: Movielens unplugged: Experiences with a recommender system on four mobile devices (2003)
Mori, G., Malik, J.: Recognizing objects in adversarial clutter: Breaking a visual CAPTCHA. In: Computer Vision and Pattern Recognition (2003)
Moy, G., Jones, N., Harkless, C., Potter, R.: Distortion estimation techniques in solving visual captchas. In: Computer Vision and Pattern Recognition (2004)
Ross, R.T.: A statistic for circular scales. Journal of Educational Psychology 29, 384–389 (1938)
Russell, J.A.: A circumplex model of affect. Journal of Personality and Social Psychology 39, 1161–1178 (1980)
Sarwar, B., Karypis, G., Konstan, J., Riedl, J.: Item-based collaborative filtering recommendation algorithms. In: The 10th International World Wide Web Conference (2001)
SparkNotes, http://community.sparknotes.com (1998–2004)
von Ahn, L., Blum, M., Langford, J.: Telling apart humans and computers automatically. Communications of the ACM 47(2), 57–60 (2004)
von Ahn, L., et al.: The ESP game, http://www.espgame.org (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Chew, M., Tygar, J.D. (2005). Collaborative Filtering CAPTCHAs. In: Baird, H.S., Lopresti, D.P. (eds) Human Interactive Proofs. HIP 2005. Lecture Notes in Computer Science, vol 3517. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427896_5
Download citation
DOI: https://doi.org/10.1007/11427896_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26001-1
Online ISBN: 978-3-540-32117-0
eBook Packages: Computer ScienceComputer Science (R0)