Type of Publication: Article in Collected Edition

Kinetic Signatures: A Systematic Investigation of Movement-Based User Identification in Virtual Reality

Author(s):

Liebers, Jonathan; Laskowski, Patrick; Rademaker, Florian; Sabel, Leon; Hoppen, Jordan; Gruenefeld, Uwe; Schneegass, Stefan

Title of Anthology:

Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24)

Publisher:

Association for Computing Machinery

Location(s):

New York, NY, USA

Publication Date:

2024

Digital Object Identifier (DOI):

doi:10.1145/3613904.3642471

Fulltext:

Kinetic Signatures: A Systematic Investigation of Movement-Based User Identification in Virtual Reality (3.94 MB)

Citation:

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Abstract

Behavioral Biometrics in Virtual Reality (VR) enable implicit user identification by leveraging the motion data of users’ heads and hands from their interactions in VR. This spatiotemporal data forms a Kinetic Signature, which is a user-dependent behavioral biometric trait. Although kinetic signatures have been widely used in recent research, the factors contributing to their degree of identifiability remain mostly unexplored. Drawing from existing literature, this work systematically examines the influence of static and dynamic components in human motion. We conducted a user study (N = 24) with two sessions to reidentify users across different VR sports and exercises after one week. We found that the identifiability of a kinetic signature depends on its inherent static and dynamic factors, with the best combination allowing for 90.91% identification accuracy after one week had passed. Therefore, this work lays a foundation for designing and refining movement-based identification protocols in immersive environments.