Continuous User Authentication Using Machine Learning on Touch Dynamics-Reference-Cited by-同舟云学术

Continuous User Authentication Using Machine Learning on Touch Dynamics

Published:2015 Issue: Volume: Page:591-598
ISSN:0302-9743
Container-title:Neural Information Processing
language:
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Author:

Budulan Ştefania,Burceanu Elena,Rebedea Traian,Chiru Costin

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-26532-2_65

Reference6 articles.

1. Feng, T., Yang, J., Yan, Z., Tapia, E.M., Shi, W.: Tips: context-aware implicit user identification using touch screen in uncontrolled environments (2014)

2. Feng, T., Liu, Z., Kwon, K.A., Shi, W., Carbunary, B., Jiangz, Y., Nguyen, N.: Continuous mobile authentication using touchscreen gestures (2012)

3. Frank, M., Biedert, R., Ma, E., Martinovic, I., Song, D.: Touchalytics: On the applicability of touchscreen input as a behavioral biometric for continuous authentication (2012)

4. Meng, Y., Duncan, S.W., Schlegel, R., Kwok, L.f.: Touch gestures based biometric authentication scheme for touchscreen mobile phones (2012)

5. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., Duchesnay, E.: Scikit-learn: machine learning in python. J. Mach. Learn. Res. 12, 2825–2830 (2011)

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