Centre for Security, Communications and Network Research

Plymouth University

Multi-Modal Behavioural Biometric Authentication for Mobile Devices

Saevanee H, Clarke NL, Furnell SM

27th IFIP International Information Security and Privacy Conference - SEC2012

Heraklion, Crete, Greece, 4-6 June, pp465-474

2012

The potential advantages of behavioural biometrics are that they can be util-ised in a transparent (non-intrusive) and continuous authentication system. However, individual biometric techniques are not suited to all users and scenar-ios. One way to increase the reliability of transparent and continuous authenti-cation systems is create a multi-modal behavioural biometric authentication sys-tem. 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 au-thentication 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%.

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