Mathis, F., Fawaz, H. I. and Khamis, M. (2020) Knowledge-driven Biometric Authentication in Virtual Reality. In: ACM CHI Conference on Human Factors in Computing Systems (CHI' 20 Extended Abstracts), Honolulu, HI, USA, 25-30 April 2020, ISBN 9781450368193 (doi: 10.1145/3334480.3382799)
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Publisher's URL: https://dl.acm.org/doi/abs/10.1145/3334480.3382799
Abstract
With the increasing adoption of virtual reality (VR) in public spaces, protecting users from observation attacks is becoming essential to prevent attackers from accessing context-sensitive data or performing malicious payment transactions in VR. In this work, we propose RubikBiom, a knowledge-driven behavioural biometric authentication scheme for authentication in VR. We show that hand movement patterns performed during interactions with a knowledge-based authentication scheme (e.g., when entering a PIN) can be leveraged to establish an additional security layer. Based on a dataset gathered in a lab study with 23 participants, we show that knowledge-driven behavioural biometric authentication increases security in an unobtrusive way. We achieve an accuracy of up to 98.91% by applying a Fully Convolutional Network (FCN) on 32 authentications per subject. Our results pave the way for further investigations towards knowledge-driven behavioural biometric authentication in VR.
| Item Type: | Conference Proceedings |
|---|---|
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Mathis, Mr Florian and Khamis, Dr Mohamed |
| Authors: | Mathis, F., Fawaz, H. I., and Khamis, M. |
| College/School: | College of Science and Engineering > School of Computing Science |
| ISBN: | 9781450368193 |
| Copyright Holders: | Copyright © 2020 by the author/owner(s). |
| Publisher Policy: | Reproduced in accordance with the publisher copyright policy |
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