Citation

Ooi, Shih Yin and Teoh, Andrew Beng Jin (2019) Touch-Stroke Dynamics Authentication Using Temporal Regression Forest. IEEE Signal Processing Letters, 26 (7). pp. 1001-1005. ISSN 1070-9908

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Abstract

Touch-stroke dynamics is a relatively recent behavioral biometrics. It authenticates an individual by observing his behavior when swiping a “stroke” on a smartphone or tablet. Several studies have attempted to determine the optimum authentication accuracy of classifiers, but none of them has used time series or temporal machine learning techniques. We postulate that when a user performs a series of touch strokes in a continuous manner, it can be perceived as a temporal behavior characteristic of the person. In this letter, we propose the use of a temporal regression forest to unearth this hidden but vital temporal information. By incorporating this temporal information in the authentication process, the proposed model is able to achieve average equal error rates of ~4.0% and ~2.5% on the Serwadda dataset and Frank dataset, respectively.

Item Type:	Article
Uncontrolled Keywords:	Touch-stroke dynamics, authentication,biometrics,temporal sequences,random regression forest
Subjects:	S Agriculture > SD Forestry
Divisions:	Faculty of Engineering and Technology (FET)
Depositing User:	Ms Suzilawati Abu Samah
Date Deposited:	09 Mar 2022 01:35
Last Modified:	09 Mar 2022 01:35
URII:	http://shdl.mmu.edu.my/id/eprint/9256

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