Skip to main content
Article thumbnail
Location of Repository

A new CAPTCHA interface design for mobile devices

By R. Lin, S-Y Huang, G.B. Bell and Y-K Lee

Abstract

This paper discusses and demonstrates the interplay between system security and user interface convenience in CAPTCHA design, and in particular, mobile device CAPTCHA design. A CAPTCHA is a computer-based security test used to distinguish human users from artificial users, preventing automated abuse of networked resources. As mobile network services improve, we can anticipate that future mobile network services will come under attack from automated programs. Importantly, while CAPTCHA techniques have existed for Internet services for some time, only limited work has been carried out to establish CAPTCHAs suitable for mobile device interfaces. The Drawing CAPTCHA (2006) is one of the most well known systems of this type. Unfortunately, though it is straightforward, it is not secure. To demonstrate this, an image-processing technique is newly proposed that breaks the Drawing CAPTCHA. A new CAPTCHA approach is then introduced here which is intended specifically for mobile devices. Experimental results suggest that this new CAPTCHA design is user-friendly as well as secure

Year: 2011
OAI identifier: oai:researchrepository.murdoch.edu.au:13406
Provided by: Research Repository

Suggested articles

Citations

  1. (2006). 2D Captchas from 3D Models.
  2. (2008). An eļ¬ƒcient segmentation algorithm for CAPTCHAs with line cluttering and character warping. Multimedia Tools and Applications.
  3. (2007). Asirra: a CAPTCHA that exploits interest-aligned manual image categorization.
  4. (2005). Computers Beat Humans at Single Character Recognition in Reading Based Human Interaction Proofs (HIPs).
  5. (2004). Distortion Estimation Techniques in Solving Visual CAPTCHAs.
  6. (2006). Drawing CAPTCHA.
  7. (2006). Face Recognition CAPTCHAs.
  8. (2005). Implicit CAPTCHAs.
  9. (2005). Is It Human or Computer? Defending E-Commerce with CAPTCHAs.
  10. (2001). Pessimal Print: A Reverse Turing Test.
  11. (2005). Recognizing Objects in Adversarial Clutter: Breaking a Visual CAPTCHA.
  12. (2005). Using Machine Learning to Break Visual Human Interaction Proofs (HIPs).

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.