Asirra: A captcha that exploits interest-aligned manual image categorization
Jeremy Elson, John R. Douceur, Jon Howell, Jared Saul · 2007
We present Asirra (Figure 1), a CAPTCHA that asks users to iden-tify cats out of a set of 12 photographs of both cats and dogs. Asirra is easy for users; user studies indicate it can be solved by humans 99.6 % of the time in under 30 seconds. Barring a major advance in machine vision, we expect computers will have no better than a 1/54,000 chance of solving it. Asirra’s image database is provided by a novel, mutually beneficial partnership with Petfinder.com. In exchange for the use of their three million images, we display an “adopt me ” link beneath each one, promoting Petfinder’s primary mission of finding homes for homeless animals. We describe the design of Asirra, discuss threats to its security, and report early de-ployment experiences. We also describe two novel algorithms for amplifying the skill gap between humans and computers that can be used on many existing CAPTCHAs.