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Permanent link (DOI): https://doi.org/10.7939/R39W0901T

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On Grey Levels in Random CAPTCHA Generation. Open Access

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Author or creator
Kouritzin, Michael
Newton, Fraser
Additional contributors
Subject/Keyword
simulation
Markov random field
statistical information compression
security
detection
image processing
Type of item
Conference/workshop Presentation
Language
English
Place
Time
Description
A CAPTCHA is an automatically generated test designed to distinguish between humans and computer programs; specifically, they are designed to be easy for humans but difficult for computer programs to pass in order to prevent the abuse of resources by automated bots. They are commonly seen guarding webmail registration forms, online auction sites, and preventing brute force attacks on passwords. In the following, we address the question: How does adding a grey level to random CAPTCHA generation affect the utility of the CAPTCHA? We treat the problem of generating the random CAPTCHA as one of random field simulation: An initial state of background noise is evolved over time using Gibbs sampling and an efficient algorithm for generating correlated random variables. This approach has already been found to yield highly-readable yet difficult-to-crack CAPTCHAs. We detail how the requisite parameters for introducing grey levels are estimated and how we generate the random CAPTCHA. The resulting CAPTCHA will be evaluated in terms of human readability as well as its resistance to automated attacks in the forms of character segmentation and optical character recognition.
Date created
2011
DOI
doi:10.7939/R39W0901T
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Rights
Copyright 2011 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.
Citation for previous publication
M. A. Kouritzin and F. Newton (2011), "On Grey Levels in Random CAPTCHA Generation", Proceedings of SPIE 8056, 80560U Visual Information Processing XX, edited by Zia-ur Rahman, Stephen E. Reichenbach, Mark A. Neifeld. doi:10.1117/12.884124
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