Abstract
A new approach to continuous authentication is presented. The method is based on a combination of statistical decision machines for brain signals. Functional Near InfraRed Spectroscopy (NIRS) is used to measure brain oxyhemoglobin changes for each subject to be authenticated. Such biosignal authentication is expected to be a viable complementary method to traditional static security systems. The designed system is based on a discriminant function which utilizes the average weight vector of one-versus-one support vector machines for NIRS spectra. By computing a histogram of Mahalanobis distances, high separability among subjects was recognized. This experimental result guarantees the utility of brain NIRS signals to the continuous authentication.
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Shozawa, M., Yokote, R., Hidano, S., Wu, CH., Matsuyama, Y. (2013). Brain Signal Based Continuous Authentication: Functional NIRS Approach. In: Rojas, I., Joya, G., Cabestany, J. (eds) Advances in Computational Intelligence. IWANN 2013. Lecture Notes in Computer Science, vol 7903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38682-4_20
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DOI: https://doi.org/10.1007/978-3-642-38682-4_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-38681-7
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