How Good are Humans at Solving CAPTCHAs? A Large Scale Evaluation
Security and Privacy (S&P)
Oakland, USA
Oakland, USA
Captchas are designed to be easy for humans but hard for machines. However, most
recent research has focused only on making them hard for machines. In this paper,
we present what is to the best of our knowledge the first large scale evaluation
of captchas from the human perspective, with the goal of assessing how much
friction captchas present to the average user.
For the purpose of this study we have asked workers from Amazon's Mechanical Turk
and an underground captcha-breaking service to solve more than 318 000 captchas
issued from the 21 most popular captcha schemes (13 images schemes and 8 audio
scheme).
Analysis of the resulting data reveals that captchas are often difficult for
humans, with audio captchas being particularly problematic. We also find some
demographic trends indicating, for example, that non-native speakers of English
are slower in general and less accurate on English-centric captcha schemes.
Evidence from a week's worth of eBay captchas (14,000,000 samples) suggests that
the solving accuracies found in our study are close to real-world values, and
that improving audio captchas should become a priority, as nearly 1% of all
captchas are delivered as audio rather than images. Finally our study also
reveals that it is more effective for an attacker to use Mechanical Turk to solve
captchas than an underground service.
- Position :
- Researcher
- Lab :
- Stanford Security Lab
- University :
- Stanford University, USA
- Email :
- Mobile :
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