13 January 2003 BaffleText: a Human Interactive Proof
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Abstract
Internet services designed for human use are being abused by programs. We present a defense against such attacks in the form of a CAPTCHA (Completely Automatic Public Turing test to tell Computers and Humans Apart) that exploits the difference in ability between humans and machines in reading images of text. CAPTCHAs are a special case of 'human interactive proofs,' a broad class of security protocols that allow people to identify themselves over networks as members of given groups. We point out vulnerabilities of reading-based CAPTCHAs to dictionary and computer-vision attacks. We also draw on the literature on the psychophysics of human reading, which suggests fresh defenses available to CAPTCHAs. Motivated by these considerations, we propose BaffleText, a CAPTCHA which uses non-English pronounceable words to defend against dictionary attacks, and Gestalt-motivated image-masking degradations to defend against image restoration attacks. Experiments on human subjects confirm the human legibility and user acceptance of BaffleText images. We have found an image-complexity measure that correlates well with user acceptance and assists in engineering the generation of challenges to fit the ability gap. Recent computer-vision attacks, run independently by Mori and Jitendra, suggest that BaffleText is stronger than two existing CAPTCHAs.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Monica Chew, Monica Chew, Henry S. Baird, Henry S. Baird, } "BaffleText: a Human Interactive Proof", Proc. SPIE 5010, Document Recognition and Retrieval X, (13 January 2003); doi: 10.1117/12.479682; https://doi.org/10.1117/12.479682
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