AN HMM-BASED BEHAVIOR MODELING APPROACH FOR CONTINUOUS MOBILE AUTHENTICATION

被引：0

作者：

Roy, Aditi ^{[1
]}

Halevi, Tzipora ^{[1
]}

Memon, Nasir ^{[1
]}

机构：

[1] NYU, Polytech Sch Engn, Brooklyn, NY 11201 USA

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | 2014年

关键词：

Touch pattern; Continuous authentication; Hidden Markov Model; Behavioral biometric; Security;

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

This paper studies continuous authentication for touch interface based mobile devices. A Hidden Markov Model (HMM) based behavioral template training approach is presented, which does not require training data from other subjects other than the owner of the mobile. The stroke patterns of a user are modeled using a continuous left-right HMM. The approach models the horizontal and vertical scrolling patterns of a user since these are the basic and mostly used interactions on a mobile device. The effectiveness of the proposed method is evaluated through extensive experiments using the Touchalytics database which comprises of touch data over time. The results show that the performance of the proposed approach is better than the state-of-the-art method.

引用

页数：5

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