Sensing-Resistance-Oriented Secure Communication in the Near-Field Region

Abstract

The advent of massive antenna arrays and intelligent surfaces in sixth-generation (6G) wireless networks opens an exciting frontier, where communication technologies in the near-field (NF) region will play a pivotal role. Given the intrinsic spatial correlation of NF channels with device and object locations, integrated sensing and communication (ISAC) emerges as a key enabler for realizing more context-aware and efficient NF communication systems. However, the evolution of ISAC also introduces a novel security challenge, which is the exposure of transmitter location information through adversarial sensing. Against this backdrop, this paper develops a twofold NF secure transmission framework to jointly protect communication confidentiality and transmitter-location privacy. Specifically, three core optimization frameworks are formulated to maximize communication security while ensuring compliance with sensing-resistance (SR) constraints, tailored to varying levels of channel state information (CSI) availability. To solve the resulting non-convex problems, generalized Rayleigh quotient and generalized singular value decomposition are leveraged to reveal tractable problem structures and decouple the interaction between communication signals and artificial noise. Simulation results validate the proposed framework and demonstrate an explicit tradeoff between secrecy enhancement and localization resilience.