NDLI: Attacks and design of image recognition CAPTCHAs

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Attacks and design of image recognition CAPTCHAs

Content Provider	ACM Digital Library
Author	Liu, Jia Cai, Kaiwei Yan, Jeff Yi, Meng Yang, Chao Zhu, Bin B. Xu, Ning Li, Qiujie
Abstract	We systematically study the design of image recognition CAPTCHAs (IRCs) in this paper. We first review and examine all existing IRCs schemes and evaluate each scheme against the practical requirements in CAPTCHA applications, particularly in large-scale real-life applications such as Gmail and Hotmail. Then we present a security analysis of the representative schemes we have identified. For the schemes that remain unbroken, we present our novel attacks. For the schemes for which known attacks are available, we propose a theoretical explanation why those schemes have failed. Next, we provide a simple but novel framework for guiding the design of robust IRCs. Then we propose an innovative IRC called Cortcha that is scalable to meet the requirements of large-scale applications. It relies on recognizing objects by exploiting the surrounding context, a task that humans can perform well but computers cannot. An infinite number of types of objects can be used to generate challenges, which can effectively disable the learning process in machine learning attacks. Cortcha does not require the images in its image database to be labeled. Image collection and CAPTCHA generation can be fully automated. Our usability studies indicate that, compared with Google's text CAPTCHA, Cortcha allows a slightly higher human accuracy rate but on average takes more time to solve a challenge.
Starting Page	187
Ending Page	200
Page Count	14
File Format	PDF
ISBN	9781450302456
DOI	10.1145/1866307.1866329
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-10-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Image recognition captcha Captcha Cortcha Human interactive proof Robustness Irc Object recognition Security Hip
Content Type	Text
Resource Type	Article

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