Designing human friendly human interaction proofs (HIPs)
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Asirra: a CAPTCHA that exploits interest-aligned manual image categorization
Proceedings of the 14th ACM conference on Computer and communications security
IEEE Security and Privacy
CAPTCHA: using hard AI problems for security
EUROCRYPT'03 Proceedings of the 22nd international conference on Theory and applications of cryptographic techniques
Building segmentation based human-friendly human interaction proofs (HIPs)
HIP'05 Proceedings of the Second international conference on Human Interactive Proofs
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Completely Automatic Public Turning test to tell Computers and Humans Apart, or CAPTCHA, is a security measure that guards a system from exploitation by the discrimination between a real human being and an automated computer program via the method of presenting to the unknown user the challenges that are hard for computer yet easy for human. Focusing on text-based CAPTCHA, this study conducted an experiment to study the effect of age groups and distortion types on the CAPTCHA task. Twenty-four participants were recruited to take part in the experiment, where twelve of them were in the senior group and twelve in the young group. Participants were observed to use three general steps: recognition, rehearsal, and motor response. With the inevitability of the security measure and the increasing population of senior netizens, this study has important implications for the design of CAPTCHA systems.