Truth in Motion: The Unprecedented Risks and Opportunities of Extended Reality Motion Data

Nair, Vivek; Rosenberg, Louis; O’Brien, James F.; Song, Dawn

doi:10.1109/msec.2023.3330392

Cited by 3 publications

(1 citation statement)

References 12 publications

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“…Based on work conducted by Miller [147], Nair et al [149] demonstrated the extent to which head and hand motion data can uniquely identify a large number of users in VR. First, they used telemetry data from BeatLeader, an open-source dataset of over 50,000 users, for both motion and context feature extraction.…”

Section: Biomechanicsmentioning

confidence: 99%

Recent Trends of Authentication Methods in Extended Reality: A Survey

Hallal,

Rhinelander,

Venkat

2024

ASI

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Extended Reality (XR) is increasingly gaining momentum in industries such as retail, health, and education. To protect users’ personal data, establishing a secure authentication system for XR devices becomes essential. Recently, the focus on authentication methods for XR devices has been limited. To further our understanding of this topic, we surveyed authentication schemes, particularly systems and methods deployed in XR settings. In this survey, we focused on reviewing and evaluating papers published during the last decade (between 2014 and 2023). We compared knowledge-based authentication, physical biometrics, behavioral biometrics, and multi-model methods in terms of accuracy, security, and usability. We also highlighted the benefits and drawbacks of those methods. These highlights will direct future Human–computer Interaction (HCI) and security research to develop secure, reliable, and practical authentication systems.

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Section: Biomechanicsmentioning

confidence: 99%

Recent Trends of Authentication Methods in Extended Reality: A Survey

Hallal,

Rhinelander,

Venkat

2024

ASI

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Deep Motion Masking for Secure, Usable, and Scalable Real-Time Anonymization of Ecological Virtual Reality Motion Data

Nair,

Guo,

O'Brien

et al. 2024

2024 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)

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Cybersecurity and Privacy Issues in Extended Reality Health Care Applications: Scoping Review

Lake,

Mc Kittrick,

Desselle

et al. 2024

JMIR XR Spatial Comput

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Background Virtual reality (VR) is a type of extended reality (XR) technology that is seeing increasing adoption in health care. There is robust evidence articulating how consumer-grade VR presents significant cybersecurity and privacy risks due to the often ubiquitous and wide range of data collection and user monitoring, as well as the unique user impact of attacks due to the immersive nature of the technology. However, little is known about how these risks translate in the use of VR systems in health care settings. Objective The objective of this scoping review is to identify potential cybersecurity risks associated with clinical XR systems, with a focus on VR, and potential mitigations for them. Methods The scoping review followed the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews), and publications were reviewed using Covidence software. The Google Scholar database was searched using the predefined search terms. The inclusion criteria of the articles were restricted to relevant primary studies published from 2017 to 2024. Furthermore, reviews, abstracts, viewpoints, opinion pieces, and low-quality studies were excluded. Additionally, data on publication statistics, topic, technology, cyber threats, and risk mitigation were extracted. These data were synthesized and analyzed using the STRIDE (spoofing, tampering, repudiation, information disclosure, denial of service, and elevation of privilege) framework, enterprise risk management framework, and National Institute of Standards and Technology Cybersecurity Framework, as well as developing threat taxonomies. Results Google Scholar returned 482 articles that matched the search criteria. After title and abstract screening, 53 studies were extracted for a full-text review, of which 29 were included for analysis. Of these, the majority were published in the last 4 years and had a focus on VR. The greatest cyber threat identified to XR components was information disclosure followed by tampering when mapped against the STRIDE framework. The majority of risk mitigation strategies provide confidentiality and integrity and can potentially address these threats. Only 3 of 29 papers mention XR in the context of health care and none of the identified threats or mitigations have been studied in a clinical setting. Conclusions This scoping review identified privacy threats where personal and health-related data may be inferred from VR usage data, potentially breaching confidentiality, as the most significant threat posited for health care VR systems. Additionally, immersive manipulation threats were highlighted, which could potentially risk user safety when launched from a compromised VR system. Many potential mitigations were identified for these threats, but these mitigations must first be assessed for their effectiveness and suitability for health care services. Furthermore, health care services should consider the usage and governance of XR for each individual application based on risk threshold and perceived benefits. Finally, it is also important to note that this scoping review was limited by the quality and scope of the studies returned by Google Scholar.

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Truth in Motion: The Unprecedented Risks and Opportunities of Extended Reality Motion Data

Cited by 3 publications

References 12 publications

Recent Trends of Authentication Methods in Extended Reality: A Survey

Recent Trends of Authentication Methods in Extended Reality: A Survey

Deep Motion Masking for Secure, Usable, and Scalable Real-Time Anonymization of Ecological Virtual Reality Motion Data

Cybersecurity and Privacy Issues in Extended Reality Health Care Applications: Scoping Review

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