Keystroke dynamics and finger knuckle imaging fusion for continuous user verification

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Abstract

The paper presents a novel user identity verification method based on fusion of keystroke dynamics and knuckle images analysis. In our solution the verification is performed by an ensemble of classifiers used to verify the identity of an active user. A proposed verification module works on a database which comprises of data representing keystroke dynamics and knuckle images. The usability of the introduced approach was tested experimentally. The obtained results confirm that the proposed fusion method gives better results than the use of a single biometric feature only. For this reason our method can be used for increasing a protection level of computer resources against impostors. The paper presents preliminary research conducted to assess the potential of biometric methods fusion.

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APA

Wesołowski, T. E., Doroz, R., Wrobel, K., & Safaverdi, H. (2017). Keystroke dynamics and finger knuckle imaging fusion for continuous user verification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10244 LNCS, pp. 141–152). Springer Verlag. https://doi.org/10.1007/978-3-319-59105-6_13

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