Abstract
Human Interactive Proofs (HIPs) are a basic security measure on the Internet to avoid several types of automatic attacks. Recently, a new HIP has been designed to increase security: the Civil Rights CAPTCHA. It employs the empathy capacity of humans to further strengthen the security of a well known OCR CAPTCHA, Securimage. In this paper, we analyse it from a security perspective, pointing out its design flaws. Then, we create a successful side-channel attack, leveraging some well-known machine learning algorithms.
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Hernández-Castro, C.J., Barrero, D.F., R-Moreno, M.D. (2015). A Machine Learning Attack against the Civil Rights CAPTCHA. In: Camacho, D., Braubach, L., Venticinque, S., Badica, C. (eds) Intelligent Distributed Computing VIII. Studies in Computational Intelligence, vol 570. Springer, Cham. https://doi.org/10.1007/978-3-319-10422-5_26
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DOI: https://doi.org/10.1007/978-3-319-10422-5_26
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10421-8
Online ISBN: 978-3-319-10422-5
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