The Authentication System for Multi-modal Behavior Biometrics Using Concurrent Pareto Learning SOM

被引：0
|
作者：
Dozono, Hiroshi [1 ]
Ito, Shinsuke [1 ]
Nakakuni, Masanori [2 ]
机构：
[1] Saga Univ, Fac Sci & Engn, 1-Honjyo, Saga 8408502, Japan
[2] Fukuoka Univ, Ctr Informat Technol, Fukuoka 8140180, Japan
来源：
ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING - ICANN 2011, PT II | 2011年 / 6792卷
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
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.
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页码：197 / +
页数：2
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