Understanding User Identification in Virtual Reality Through Behavioral Biometrics and the Effect of Body Normalization

Liebers, Jonathan; Abdelaziz, Mark; Mecke, Lukas; Saad, Alia; Auda, Jonas; Gruenefeld, Uwe; Alt, Florian; Schneegaß, Stefan

doi:10.1145/3411764.3445528

Cited by 54 publications

(27 citation statements)

References 29 publications

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“…For instance, Miller et al [3] used the raw Y-axis of the Head Sensor (i.e., roughly the person's height) as a principal descriptor for user identity. However, as pointed out by the authors and recent literature [9], such a feature is not persistent. Last, the comprehension of which factors impact profiling in XR technologies is currently limited.…”

Section: Introductionmentioning

confidence: 48%

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You Can’t Hide Behind Your Headset: User Profiling in Augmented and Virtual Reality

et al. 2023

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Section: Introductionmentioning

confidence: 48%

“…Last, the comprehension of which factors impact profiling in XR technologies is currently limited. Indeed, the literature suggests that profiling performances might depend on the technology (i.e., AR, VR) [10], user actions [4], cognitive workload [11], experimental bias [9], and XR sensors [4], but they were never examined altogether.…”

Section: Introductionmentioning

confidence: 99%

You Can’t Hide Behind Your Headset: User Profiling in Augmented and Virtual Reality

et al. 2023

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“…Implicit Authentication. Functional biometrics, such as toothprint in ToothSonic, could be naturally combined with implicit authentication to enable some emerging applicaiton [25,35,60]. Toothprint could be the desired approach for interaction methods in VR and AR applications to enable implicit authentication.…”

Section: Limitations and Discussionmentioning

confidence: 99%

Earable Authentication via Acoustic Toothprint

Wang

Ren

Chen

et al. 2021

Proceedings of the 2021 ACM SIGSAC Conference on Computer and Communications Security

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Earables (ear wearable) are rapidly emerging as a new platform encompassing a diverse range of personal applications. The traditional authentication methods hence become less applicable and inconvenient for earables due to their limited input interface. Nevertheless, earables often feature rich around-the-head sensing capability that can be leveraged to capture new types of biometrics. In this work, we propose ToothSonic that leverages the toothprint-induced sonic effect produced by a user performing teeth gestures for earable authentication. In particular, we design representative teeth gestures that can produce effective sonic waves carrying the information of the toothprint. To reliably capture the acoustic toothprint, it leverages the occlusion effect of the ear canal and the inward-facing microphone of the earables. It then extracts multi-level acoustic features to reflect the intrinsic toothprint information for authentication. The key advantages of ToothSonic are that it is suitable for earables and is resistant to various spoofing attacks as the acoustic toothprint is captured via the user's private teeth-ear channel that modulates and encrypts the sonic waves. Our experiment studies with 25 participants show that ToothSonic achieves up to 95% accuracy with only one of the users' tooth gestures.CCS Concepts: • Security and privacy ✙ Biometrics; • Human-centered computing ✙ Ubiquitous and mobile computing systems and tools;

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“…Type Data acquisition and device Algorithms Dataset and results Additionally, we found six papers (Pfeuffer et al, 2019;Miller M. R. et al, 2020;Miller R. et al, 2020;Liebers et al, 2021;Miller et al, 2021;Schell et al, 2022) focusing on VR authentication that are not included in the review of Jones et al An overview of these papers is listed in Table 5.…”

Section: Referencesmentioning

confidence: 99%

Digital body, identity and privacy in social virtual reality: A systematic review

Lin

Latoschik

2022

Front. Virtual Real.

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Social Virtual Reality (social VR or SVR) provides digital spaces for diverse human activities, social interactions, and embodied face-to-face encounters. While our digital bodies in SVR can in general be of almost any conceivable appearance, individualized or even personalized avatars bearing users’ likeness recently became an interesting research topic. Such digital bodies show a great potential to enhance the authenticity of social VR citizens and increase the trustworthiness of interpersonal interaction. However, using such digital bodies might expose users to privacy and identity issues such as identity theft: For instance, how do we know whether the avatars we encounter in the virtual world are who they claim to be? Safeguarding users’ identities and privacy, and preventing harm from identity infringement, are crucial to the future of social VR. This article provides a systematic review on the protection of users’ identity and privacy in social VR, with a specific focus on digital bodies. Based on 814 sources, we identified and analyzed 49 papers that either: 1) discuss or raise concerns about the addressed issues, 2) provide technologies and potential solutions for protecting digital bodies, or 3) examine the relationship between the digital bodies and users of social VR citizens. We notice a severe lack of research and attention on the addressed topic and identify several research gaps that need to be filled. While some legal and ethical concerns about the potential identity issues of the digital bodies have been raised, and despite some progress in specific areas such as user authentication has been made, little research has proposed practical solutions. Finally, we suggest potential future research directions for digital body protection and include relevant research that might provide insights. We hope this work could provide a good overview of the existing discussion, potential solutions, and future directions for researchers with similar concerns. We also wish to draw attention to identity and privacy issues in social VR and call for interdisciplinary collaboration.

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Understanding User Identification in Virtual Reality Through Behavioral Biometrics and the Effect of Body Normalization

Cited by 54 publications

References 29 publications

You Can’t Hide Behind Your Headset: User Profiling in Augmented and Virtual Reality

You Can’t Hide Behind Your Headset: User Profiling in Augmented and Virtual Reality

Earable Authentication via Acoustic Toothprint

Digital body, identity and privacy in social virtual reality: A systematic review

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