Problem
Research questions and friction points this paper is trying to address.
Extended Reality
Healthcare
Privacy
Security
Risk Assessment
XR-PRISM: Data-Driven Privacy and Risk Impact Scoring Metric for Extended Reality in Healthcare
🤖 AI Summary
This study addresses the absence of a unified risk quantification framework in current medical extended reality (XR) systems, which hinders effective assessment and prioritization of security and privacy threats. Through a systematic review of 65 studies, the authors develop a four-layer threat taxonomy encompassing device, network, user, and cloud components, and propose XR-PRISM—a novel, six-factor weighted risk scoring model tailored to medical XR. XR-PRISM enables transparent, data-driven evaluation and prioritization of risks. The analysis reveals that over 70% of existing countermeasures lack standardized evaluation, and fewer than 15% of identified attacks require high levels of technical expertise. This work provides a practical, quantifiable decision-support tool for risk management in medical XR deployments.
📝 Abstract
Extended Reality (XR) technologies are transforming healthcare through immersive training, remote consultation, and patient rehabilitation. However, their extensive sensing capabilities and complex data pipelines introduce distinct security, privacy, and safety risks. Existing research lacks a unified quantitative framework for assessing and prioritizing these risks. We review 65 peer-reviewed studies on XR security and privacy published from 2017 to 2024, synthesizing a four-layer threat taxonomy consisting of Device, Network, User, and Cloud layers, along with a corresponding catalog of defenses. Building on this analysis, we introduce XR-PRISM, a six-factor weighted Privacy and Risk Impact Scoring Metric that integrates threat likelihood, system vulnerability, attack surface, safety impact, privacy impact, and control effectiveness into a single actionable risk score. Our analysis shows that more than 70% of the identified countermeasures lack standardized risk evaluation, while fewer than 15% of the documented attacks require a high level of expertise to execute. XR-PRISM provides researchers and practitioners with a transparent, data-driven method for comparing, prioritizing, and mitigating security and privacy risks in healthcare XR deployments.
Innovation
Methods, ideas, or system contributions that make the work stand out.
XR-PRISM
risk scoring metric
extended reality
healthcare privacy
threat taxonomy
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