Title

Multimodal behavioural biometric authentication for mobile devices

Document Type

Conference Proceeding

Publisher

Springer

Faculty

Faculty of Computing, Health and Science

School

ECU Security Research Institute

RAS ID

14549

Comments

This article was originally published as: Saevanee, H., Clarke, N. , & Furnell, S. (2012). Multimodal behavioural biometric authentication for mobile devices. Proceedings of 27th IFIP International Information Security and Privacy Conference. (pp. 465-474). Crete, Greece. Springer. Original article available here

Abstract

The potential advantages of behavioural biometrics are that they can be utilised in a transparent (non-intrusive) and continuous authentication system. However, individual biometric techniques are not suited to all users and scenarios. One way to increase the reliability of transparent and continuous authentication systems is create a multi-modal behavioural biometric authentication system. This research investigated three behavioural biometric techniques based on SMS texting activities and messages, looking to apply these techniques as a multi-modal biometric authentication method for mobile devices. The results showed that behaviour profiling, keystroke dynamics and linguistic profiling can be used to discriminate users with overall error rates 20%, 20% and 22% respectively. To study the feasibility of multi-modal behaviour biometric authentication system, matching-level fusion methods were applied. Two fusion methods were utilised: simple sum and weight average. The results showed clearly that matching-level fusion can improve the classification performance with an overall EER 8%.

DOI

10.1007/978-3-642-30436-1_38

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