Intelligent Surface Assisted Radar Stealth Against Unauthorized ISAC

TL;DR

This work tackles privacy leakage in ISAC networks by deploying an intelligent surface (IS) to distort the AoA estimation of an unauthorized dual-functional base station (DFBS) while preserving downlink communication quality. The authors formulate the anti-sensing objective as maximizing AoA distortion under a required SNR constraint and recast the nonconvex problem into an inner-product utility, enabling a closed-form, geometry-based solution. A ν-parameterization and projection onto a feasible circular region yield a tractable algorithm that computes IS phase shifts and recovers the IS configuration with a direct closed-form mapping. Simulations demonstrate that the proposed method approaches the performance of an exhaustive search and outperforms a max-inner baseline, providing a practical, passive mechanism to enhance privacy in 6G ISAC environments with limited degradation to communication performance.

Abstract

The integration of radar sensors and communication networks as envisioned for the 6G wireless networks poses significant security risks, e.g., the user position information can be released to an unauthorized dual-functional base station (DFBS). To address this issue, we propose an intelligent surface (IS)-assisted radar stealth technology that prevents adversarial sensing. Specifically, we modify the wireless channels by tuning the phase shifts of IS in order to protect the target user from unauthorized sensing without jeopardizing the wireless communication link. In principle, we wish to maximize the distortion between the estimated angle-of-arrival (AoA) by the DFBS and the ground truth given the minimum signal-to-noise-radio (SNR) constraint for communication. Toward this end, we propose characterizing the problem as a game played by the DFBS and the IS, in which the DFBS aims to maximize a particular utility while the IS aims to minimize the utility. Although the problem is nonconvex, this paper shows that it can be optimally solved in closed form from a geometric perspective. According to the simulations, the proposed closed-form algorithm outperforms the baseline methods significantly in combating unauthorized sensing while limiting the impacts on wireless communications.

Figures (10)

• Figure 1:
• Figure 2:
• Figure 4: Feasible region of $\nu$ in problem \ref{['eqn transform problem second']}.
• Figure 5: Network topology of our simulations.
• Figure 6:

Theorems & Definitions (2)

• Lemma 1
• proof