Secure Design for Integrated Sensing and Semantic Communication System

This paper investigates the secure resource allocation for a downlink integrated sensing and communication system with multiple legal users and potential eavesdroppers. In the considered model, the base station (BS) simultaneously transmits sensing and communication signals through beamforming design, where the sensing signals can be viewed as artificial noise to enhance the security of communication signals. To further enhance the security in the semantic layer, the semantic information is extracted from the original information before transmission. The user side can only successfully recover the received information with the help of the knowledge base shared with the BS, which is stored in advance. Our aim is to maximize the sum semantic secrecy rate of all users while maintaining the minimum quality of service for each user and guaranteeing overall sensing performance. To solve this sum semantic secrecy rate maximization problem, an iterative algorithm is proposed using the alternating optimization method. The simulation results demonstrate the superiority of the proposed algorithm in terms of secure semantic communication and reliable detection.

I. Introduction

The bottleneck of spectrum shortage is brought on by the proliferation of emerging applications with high data-rate requirements, such as virtual reality, holographic communication, and high-mobility sensing [1]. To meet the strict requirements in emerging applications, three functions must be synchronized, i.e., mobile sensing, communication, and computation. While these three functions operate independently in conventional wireless networks, they cannot meet the demands of the sixth-generation (6G) communication system including immersive communication, hyper-reliable and low latency communications, integrated sensing and communication, and integrated AI and communication.