Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)

Chellapilla, Kumar, Simard, Patrice Y.

Neural Information Processing Systems 

Machine learning is often used to automatically solve human tasks. In this paper, we look for tasks where machine learning algorithms are not as good as humans with the hope of gaining insight into their current limitations. We studied various Human Interactive Proofs (HIPs) on the market, because they are systems designed to tell computers and humans apart by posing challenges presumably too hard for computers. We found that most HIPs are pure recognition tasks which can easily be broken using machine learning.

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