Cybersecurity and Privacy Challenges in Extended Reality: Threats, Solutions, and Risk Mitigation Strategies

Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), enables immersive experiences across various fields, including entertainment, healthcare, and education. However, its data-intensive and interactive nature introduces significant cybersecurity and privacy challenges. This paper presents a detailed adversary model to identify threat actors and attack vectors in XR environments. We analyze key risks, including identity theft and behavioral data leakage, which can lead to profiling, manipulation, or invasive targeted advertising. To mitigate these risks, we explore technical solutions such as Advanced Encryption Standard (AES), Rivest–Shamir–Adleman (RSA), and Elliptic Curve Cryptography (ECC) for secure data transmission, multi-factor and biometric authentication, data anonymization techniques, and AI-driven anomaly detection for real-time threat monitoring. A comparative benchmark evaluates these solutions’ practicality, strengths, and limitations in XR applications. The findings emphasize the need for a holistic approach, combining robust technical measures with privacy-centric policies, to secure XR ecosystems and ensure user trust.

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Publication Details

Journal
Virtual Worlds
Published
2024-12-30
DOI
https://doi.org/10.3390/virtualworlds4010001
Citations
17
Primary Topic
Virtual Reality Applications and Impacts
Type
article
Field-Weighted Citation Impact
6.33
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article

Cybersecurity and Privacy Challenges in Extended Reality: Threats, Solutions, and Risk Mitigation Strategies

Mohammed El‐Hajj
17 citations
Virtual Worlds
Virtual Reality Applications and Impacts
6.33
article

Cybersecurity and Privacy Challenges in Extended Reality: Threats, Solutions, and Risk Mitigation Strategies

Mohammed El‐Hajj
article en
17 citations

Abstract

Extended Reality (XR), encompassing Augmented Reality (AR), Virtual Reality (VR), and Mixed Reality (MR), enables immersive experiences across various fields, including entertainment, healthcare, and education. However, its data-intensive and interactive nature introduces significant cybersecurity and privacy challenges. This paper presents a detailed adversary model to identify threat actors and attack vectors in XR environments. We analyze key risks, including identity theft and behavioral data leakage, which can lead to profiling, manipulation, or invasive targeted advertising. To mitigate these risks, we explore technical solutions such as Advanced Encryption Standard (AES), Rivest–Shamir–Adleman (RSA), and Elliptic Curve Cryptography (ECC) for secure data transmission, multi-factor and biometric authentication, data anonymization techniques, and AI-driven anomaly detection for real-time threat monitoring. A comparative benchmark evaluates these solutions’ practicality, strengths, and limitations in XR applications. The findings emphasize the need for a holistic approach, combining robust technical measures with privacy-centric policies, to secure XR ecosystems and ensure user trust.

Virtual WorldsVol. 4(1)
Arab Open University (LB), University of Twente (NL)
Openalex Percentile: Top 3%
Virtual Reality Applications and Impacts
6.33
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