Integrated Identity Protection for Semantic Communications in Embodied IoT Systems

Abstract

Embodied Internet of Things (IoT) systems are promoting the adoption of task-oriented semantic communication (SemCom), in which the trustworthy task decisions increasingly require both semantic reliability and source legitimacy. However, existing trustworthy SemCom designs mainly focus on semantic content recovery and protection, with limited attention to source identity protection. Motivated by this limitation, this paper establishes a new information exploitation perspective for integrated SemCom-identity protection that leverages task-level error tolerance to coordinate semantic information and source identity information carried by the same waveform. We first examine these two information resources and then analyze their integration feasibility at the observation, processing, and decision levels. To exploit these resources for different identity protection objectives, we further develop a dual-branch identity protection mechanism with two operating modes. In the authentication mode, semantic recovery and physical-layer source verification are performed in parallel using the same received observation. In the concealment mode, identity exposure is suppressed while semantic reconstruction quality is maintained to support anonymous transmission. Finally, two representative case studies on active source impersonation and passive identity inference are presented to evaluate the proposed framework.