Artificial Noise-aided Integrated Sensing and Communication Networks: Performance Analysis and Security Enhancement

Despite its great potential in next-generation network applications, the integrated sensing and communication (ISAC) network suffers from security challenges stemming from shared spectrum and the inherent openness of wireless channels. To tackle this emerging challenge, this paper investigates the integration of artificial noise (AN) security technology into ISAC networks. A unified analytical framework utilizing stochastic geometry is developed to analyze the trade-offs between sensing and communication performance. The framework incorporates comprehensive 3D spatial modeling essential for aerial-terrestrial integration scenarios. Closed-form expressions for the probability of detection and coverage are derived, enabling quantitative analysis of performance limits under constrained wireless resources. The proposed AN-ISAC architecture incorporates artificial noise for enhanced security, addressing privacy leakage and eavesdropping threats without complex key management. Simulation results validate the theoretical models, highlighting the architecture’s effectiveness in maintaining high security and performance standards in dynamic network environments. Analysis reveals optimal operating boundaries where artificial noise strategically balances security enhancement against sensing and communication functionality. Distance-optimized AN deployment and height-aware resource allocation demonstrate significant performance improvements over conventional approaches. This work establishes critical foundations for practical secure ISAC deployments, with future research extending to mobile aerial networks and adaptive interference management.