We present a technique for using a content-based video labeling task as a CAPTCHA.
Our video CAPTCHAs are generated from YouTube videos, which contain labels (tags)
supplied by the person that uploaded the video. They are graded using a video's
tags, as well as tags from related videos. In a user study involving 184
participants, we were able to increase the average human success rate on our video
CAPTCHA from roughly 70% to 90%, while keeping the average success rate of a tag
frequency-based attack fixed at around 13%. Through a different parameterization of
the challenge generation and grading algorithms, we were able to reduce the success
rate of the same attack to 2%, while still increasing the human success rate from
70% to 75%. The usability and security of our video CAPTCHA appears to be
comparable to existing CAPTCHAs, and a majority of participants (60%) indicated
that they found the video CAPTCHAs more enjoyable than traditional CAPTCHAs in
which distorted text must be transcribed.