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Biometric Counter-spoofing for Mobile Devices using Gaze Information

Ali, Asad, Alsufyani, Nawal, Hoque, Sanaul, Deravi, Farzin (2017) Biometric Counter-spoofing for Mobile Devices using Gaze Information. In: Pattern Recognition and Machine Intelligence. . pp. 11-18. Springer (doi:10.1007/978-3-319-69900-4_2) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:63352)

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With the rise in the use of biometric authentication on mobile devices, it is important to address the security vulnerability of spoofing attacks where an attacker using an artefact representing the biometric features of a genuine user attempts to subvert the system. In this paper, techniques for presentation attack detection are presented using gaze information with a focus on their applicability for use on mobile devices. Novel features that rely on directing the gaze of the user and establishing its behaviour are explored for detecting spoofing attempts. The attack scenarios considered in this work include the use of projected photos, 2D and 3D masks. The proposed features and the systems based on them were extensively evaluated using data captured from volunteers performing genuine and spoofing attempts. The results of the evaluations indicate that gaze-based features have the potential for discriminating between genuine attempts and imposter attacks on mobile devices.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1007/978-3-319-69900-4_2
Uncontrolled keywords: Biometrics, Spoofing, Presentation Attacks, Mobile Security, Liveness Detection
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Farzin Deravi
Date Deposited: 09 Sep 2017 10:35 UTC
Last Modified: 16 Feb 2021 13:48 UTC
Resource URI: (The current URI for this page, for reference purposes)
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