The authentication system for multi-modal behavior biometrics using concurrent Pareto learning SOM

Authors:
Hiroshi Dozono;Shinsuke Ito;Masanori Nakakuni
Affiliations:
Faculty of Science and Engineering, Saga University, Saga, Japan;Faculty of Science and Engineering, Saga University, Saga, Japan;Information Technology Center, Fukuoka University, Fukuoka, Japan
Venue:
ICANN'11 Proceedings of the 21st international conference on Artificial neural networks - Volume Part II
Year:
2011

Citing 2
Cited 0

Concurrent Self-Organizing Maps for Pattern Classification

ICCI '02 Proceedings of the 1st IEEE International Conference on Cognitive Informatics
Guide to Biometrics

Guide to Biometrics

Quantified Score

Hi-index	0.01

Visualization

Abstract

We have proposed the integration of behavior biometrics using Supervised Pareto learning SOM to improve the accuracy of authentication. For small systems such as mobile devices, this method may be heavy, because of the memory usage or computational power. In this paper, we propose the application of Concurrent Pareto learning SOM, which uses a small map for each user. The performance of this method is confirmed by authentication experiments using behavior biometrics of keystroke timings and key typing sounds.