CueVR: Studying the Usability of Cue-based Authentication for Virtual Reality

Abdelrahman, Y., Mathis, F., Knierim, P., Kettler, A., Alt, F. and Khamis, M. (2022) CueVR: Studying the Usability of Cue-based Authentication for Virtual Reality. In: 2022 International Conference on Advanced Visual Interfaces (AVI 2022), Rome, Italy, 06-10 Jun 2022, p. 34. ISBN 9781450397193 (doi: 10.1145/3531073.3531092)

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Abstract

Existing virtual reality (VR) authentication schemes are either slow or prone to observation attacks. We propose CueVR, a cue-based authentication scheme that is resilient against observation attacks by design since vital cues are randomly generated and only visible to the user experiencing the VR environment. We investigate three different input modalities through an in-depth usability study (N=20) and show that while authentication using CueVR is slower than the less secure baseline, it is faster than existing observation resilient cue-based schemes and VR schemes (4.151 s – 7.025 s to enter a 4-digit PIN). Our results also indicate that using the controllers’ trackpad significantly outperforms input using mid-air gestures. We conclude by discussing how visual cues can enhance the security of VR authentication while maintaining high usability. Furthermore, we show how existing real-world authentication schemes combined with VR’s unique characteristics can advance future VR authentication procedures.

Item Type:Conference Proceedings
Additional Information:This work has been funded, in part, by an EPSRC New Investigator Award (EP/V008870/1), by PETRAS National Centre of Excellence for IoT Systems Cybersecurity EPSRC (EP/S035362/1), by the University of Edinburgh and the University of Glasgow jointly funded PhD studentships, by the German Research Foundation (DFG) project no. 425869382, and by dtec.bw– Digitalization and Technology Research Center of the Bundeswehr [Voice of Wisdom].
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Mathis, Mr Florian and Khamis, Dr Mohamed
Authors: Abdelrahman, Y., Mathis, F., Knierim, P., Kettler, A., Alt, F., and Khamis, M.
College/School:College of Science and Engineering > School of Computing Science
ISBN:9781450397193
Copyright Holders:Copyright © 2022 ACM
First Published:First published in AVI 2022: Proceedings of the 2022 International Conference on Advanced Visual Interfaces Article no.: 34:1–9
Publisher Policy:Reproduced in accordance with the publisher copyright policy
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