Cross-Layer Management Framework for Enhancing XR-Based System Security in Zero-Trust Wireless Communications

Extended reality (XR) and 6G networks are set to transform mobile immersive experiences, with privacy and security being paramount in XR communications. Achieving secure and reliable XR experiences while meeting high-resolution and low-latency requirements is challenging for wireless networks. A novel security-aware cross-layer communication management framework is proposed, employing zero-trust spatiotemporal physical layer level manipulations for moving-target defense. Driven by deep reinforcement learning and real-time monitoring, the proposed framework adaptively reprograms the network configuration to maximize the user’s quality of experience (QoE), reduce the overall latency, and minimize the attacker’s intercept probability. The framework was evaluated in a simulated scenario featuring an indirect multi-hop communication setup. The results show that the proposed framework effectively and efficiently secures XR user communications while maintaining QoE, outperforming conventional Q-learning algorithms.

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Publication Details

Journal
IEEE Journal on Selected Areas in Communications
Published
2025-04-21
DOI
https://doi.org/10.1109/jsac.2025.3560004
Citations
2
Primary Topic
IoT and Edge/Fog Computing
Type
article
Field-Weighted Citation Impact
2.97
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article

Cross-Layer Management Framework for Enhancing XR-Based System Security in Zero-Trust Wireless Communications

Sami Muhaidat, Mahmoud Al‐Qutayri, Esraa M. Ghourab, Denis Gračanin et al.
2 citations
IEEE Journal on Selected Areas in Communications
IoT and Edge/Fog Computing
2.97
article

Cross-Layer Management Framework for Enhancing XR-Based System Security in Zero-Trust Wireless Communications

Sami Muhaidat, Mahmoud Al‐Qutayri, Esraa M. Ghourab, Denis Gračanin, Mohamed Azab
article en
2 citations

Abstract

Extended reality (XR) and 6G networks are set to transform mobile immersive experiences, with privacy and security being paramount in XR communications. Achieving secure and reliable XR experiences while meeting high-resolution and low-latency requirements is challenging for wireless networks. A novel security-aware cross-layer communication management framework is proposed, employing zero-trust spatiotemporal physical layer level manipulations for moving-target defense. Driven by deep reinforcement learning and real-time monitoring, the proposed framework adaptively reprograms the network configuration to maximize the user’s quality of experience (QoE), reduce the overall latency, and minimize the attacker’s intercept probability. The framework was evaluated in a simulated scenario featuring an indirect multi-hop communication setup. The results show that the proposed framework effectively and efficiently secures XR user communications while maintaining QoE, outperforming conventional Q-learning algorithms.

IEEE Journal on Selected Areas in CommunicationsVol. 43(6)
Khalifa University of Science and Technology (AE), Virginia Military Institute (US), Virginia Tech (US)
Openalex Percentile: Top 9%
IoT and Edge/Fog Computing
2.97
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Cross-Layer Management Framework for Enhancing XR-Based System Security in Zero-Trust Wireless Communications — Sami Muhaidat, Mahmoud Al‐Qutayri, et al. · IEEE Journal on Selected Areas in Communications (2025) | TGRS Research Map | TGRS