在零信任无线通信中增强基于 XR 的系统安全的跨层管理框架

Esraa M. Ghourab;Mohamed Azab;Denis Gračanin;Mahmoud Al-Qutayri;Sami Muhaidat
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引用次数: 0

摘要

扩展现实(XR)和6G网络将改变移动沉浸式体验,隐私和安全在XR通信中至关重要。在满足高分辨率和低延迟要求的同时,实现安全可靠的XR体验对无线网络来说是一项挑战。提出了一种新的安全感知跨层通信管理框架,采用零信任时空物理层操作实现移动目标防御。在深度强化学习和实时监控的驱动下,该框架自适应地重新编程网络配置,以最大限度地提高用户体验质量(QoE),减少整体延迟,并最大限度地降低攻击者的拦截概率。该框架在具有间接多跳通信设置的模拟场景中进行了评估。结果表明,该框架在保持QoE的同时有效地保护了XR用户通信,优于传统的q -学习算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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