GazeRoomLock: Using Gaze and Head-Pose to Improve the Usability and Observation Resistance of 3D Passwords in Virtual Reality

George, C., Buschek, D., Ngao, A. and Khamis, M. (2020) GazeRoomLock: Using Gaze and Head-Pose to Improve the Usability and Observation Resistance of 3D Passwords in Virtual Reality. In: 7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics (AVR 2020), Lecco, Italy, 7-10 Sept 2020, pp. 61-81. ISBN 978-030584641 (doi: 10.1007/978-3-030-58465-8_5)

Abstract

Authentication has become an important component of Immersive Virtual Reality (IVR) applications, such as virtual shopping stores, social networks, and games. Recent work showed that compared to traditional graphical and alphanumeric passwords, a more promising form of passwords for IVR is 3D passwords. This work evaluates four multimodal techniques for entering 3D passwords in IVR that consist of multiple virtual objects selected in succession. Namely, we compare eye gaze and head pose for pointing, and dwell time and tactile input for selection. A comparison of a) usability in terms of entry time, error rate, and memorability, and b) resistance to real world and offline observations, reveals that: multimodal authentication in IVR by pointing at targets using gaze, and selecting them using a handheld controller significantly improves usability and security compared to the other methods and to prior work. We discuss how the choice of pointing and selection methods impacts the usability and security of 3D passwords in IVR.

• Item Type: Conference Proceedings
• Additional Information: The contributions from the authors Mohamed Khamis and Daniel Buschek were supported, in part, by the Royal Society of Edinburgh (Award number 65040), and the Bavarian State Ministry of Science and the Arts in the framework of the Centre Digitisation.Bavaria (ZD.B).
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Buschek, Daniel and Khamis, Dr Mohamed
• Authors: George, C., Buschek, D., Ngao, A., and Khamis, M.
• College/School: College of Science and Engineering; College of Science and Engineering > School of Computing Science
• ISSN: 0302-9743
• ISBN: 978-030584641
• Published Online: 31 August 2020
• Copyright Holders: Copyright © Springer Nature Switzerland AG 2020
• First Published: First published in Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2020. Lecture Notes in Computer Science, vol 12242
• Publisher Policy: Reproduced in accordance with the publisher copyright policy