Abstract
In this paper, we provide an approach for authenticating users in virtual reality (VR) environments by tracking the behavior of users as they perform goal-oriented tasks, such as throwing a ball at a target. With the pervasion of VR in mission-critical applications such as manufacturing, navigation, military training, education, and therapy, validating the identity of users using VR systems is becoming paramount to prevent tampering of the VR environments, and to ensure user safety. Unlike prior work, which uses PIN and pattern based passwords to authenticate users in VR environments, our approach authenticates users based on their natural interactions within the virtual space by matching the 3D trajectory of the dominant hand gesture controller in a display-based head-mounted VR system to a library of trajectories. To handle natural differences in wait times between multiple parts of an action such as picking a ball and throwing it, our matching approach uses a symmetric sum-squared distance between the nearest neighbors across the query and library trajectories. Our work enables seamless authentication without requiring the user to stop their activity and enter specific credentials, and can be used to continually validate the identity of the user. We conduct a pilot study with 14 subjects throwing a ball at a target in VR using the gesture controller and achieve a maximum accuracy of 92.86% by comparing to a library of 10 trajectories per subject, and 90.00% by comparing to 6 trajectories per subject.
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Acknowledgements
This work was partially supported by the National Science Foundation (NSF) grant #1730183. We acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research.
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Kupin, A., Moeller, B., Jiang, Y., Banerjee, N.K., Banerjee, S. (2019). Task-Driven Biometric Authentication of Users in Virtual Reality (VR) Environments. In: Kompatsiaris, I., Huet, B., Mezaris, V., Gurrin, C., Cheng, WH., Vrochidis, S. (eds) MultiMedia Modeling. MMM 2019. Lecture Notes in Computer Science(), vol 11295. Springer, Cham. https://doi.org/10.1007/978-3-030-05710-7_5
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