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Breaking Visual CAPTCHAs with Naive Pattern Recognition Algorithms

Lookup NU author(s): Dr Jeff Yan, Ahmad El Ahmad


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Visual CAPTCHAs have been widely used across the Internet to defend against undesirable or malicious bot programs. In this paper, we document how we have broken most such visual schemes provided at, a publicly available web service for CAPTCHA generation. These schemes were effectively resistant to attacks conducted using a high-quality Optical Character Recognition program, but were broken with a near 100% success rate by our novel attacks. In contrast to early work that relied on sophisticated computer vision or machine learning algorithms, we used simple pattern recognition algorithms but exploited fatal design errors that we discovered in each scheme. Surprisingly, our simple attacks can also break many other schemes deployed on the Internet at the time of writing: their design had similar errors. We also discuss defence against our attacks and new insights on the design of visual CAPTCHA schemes.

Publication metadata

Author(s): Yan J, Salah El Ahmad A

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: Proceedings of the 23rd Annual Computer Security Applications Conference (ACSAC)

Year of Conference: 2007

Pages: 279-291

ISSN: 1063-9527

Publisher: IEEE


DOI: 10.1109/ACSAC.2007.47

Library holdings: Search Newcastle University Library for this item

ISBN: 9780769530604