SGPL: An Intelligent Game-Based Secure Collaborative Communication Scheme for Metaverse Over 5G and Beyond Networks

计算机科学 虚拟实境 斯塔克伯格竞赛 干扰 人机交互 分布式计算 计算机安全 虚拟现实 数学 物理 数理经济学 热力学
作者
Miaojiang Chen,Anfeng Liu,Naixue Xiong,Houbing Song,Victor C. M. Leung
出处
期刊:IEEE Journal on Selected Areas in Communications [Institute of Electrical and Electronics Engineers]
卷期号:42 (3): 767-782 被引量:35
标识
DOI:10.1109/jsac.2023.3345403
摘要

Human-centric communication metaverse relies on the convergent integration of multiple existing technologies such as 5G and beyond networks, virtual reality, augmented reality, and digital twins, and thus their security vulnerabilities and vulnerability to interference attacks may also be inherited by the metaverse. In particular, existing security policies may be inefficient for communication interference problems encountered in multi-device collaborative computing in a metaverse 5G environment and lack adaptability to metaverse applications. In this paper, we propose a novel intelligent game anti-interference collaborative computing model that accurately describes the interference relationships among source devices, cooperating devices, and interferers in metaverse collaborative computing. We model the offensive and defensive confrontation between multiple metaverse devices as a Stackelberg game, where the source device is the leader, the collaborative computing device acts as the sub-leader, adjusts its antijamming strategy according to the source device's strategy to improve the source device's communication anti-jamming performance, and the jammer acts as the follower. We design an intelligent Stackelberg Game-theoretic Policy-based Learning (SGPL) algorithm for jamming resistance in metaverses over 5G and Beyond Networks, where the leaders (co-computing devices) update their training parameters using the total derivatives of the objective function, while the followers (i.e., jammers) update their training parameters using an independent gradient dynamics strategy. Loops are eased and convergence is accelerated by introducing differential dynamics into the leader training network to reflect the interaction structure of the critic and actor network layers. Finally, numerical results demonstrate the effectiveness of the proposed SGPL algorithm in metaverse anti-jamming countermeasures. The proposed SGPL algorithm has the potential to be generalized to other metaverse applications with multi-user attack and defense characteristics.
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