Abstract:

With the rapid advancement of integrated communication-sensing technology in future 6G networks, the deep integration of communication and sensing functions not only enhances system performance but also introduces multidimensional security challenges. From a security perspective, this paper analyzes the composite security risks of integrated communication-sensing systems at the physical layer, privacy protection, and in traditional communication versus 6G new scenarios. Specifically, physical layer security faces threats such as channel state spoofing, environmental reflection manipulation, and joint attacks on communication and sensing signals. Privacy protection requires addressing risks of user location information leakage, behavioral trajectory exposure, and high-dimensional sensing data breaches. Simultaneously, the system must still meet fundamental security requirements including identity authentication, data integrity, and low-latency interaction. To address these security needs, key technological advancements are summarized, including lightweight RF fingerprint authentication, deep learning-based anomaly detection, perception data protection combining differential privacy and federated learning, resource regulation and joint scheduling mechanisms driven by deep reinforcement learning, as well as blockchain-based distributed trust management and lightweight edge collaboration strategies. By integrating these technologies, system-level security safeguards can be established across multiple dimensions including physical layer, data processing, resource management, and cross-domain collaboration, providing theoretical support and technical references for secure and trustworthy operation of integrated communication-sensing systems in high-dynamic, high-density, and strongly real-time environments.

Key words: intelligent integration, physical layer security, privacy protection, intelligent resource allocation, blockchain