Intelligent Surface Assisted Radar Stealth Against Unauthorized ISAC

2025-01-26

AI Summary

To address security threats posed by illegal dual-functional base stations (DFBSs) in 6G integrated sensing and communication (ISAC) systems—specifically, their exploitation of radar sensing to infer user location—this paper proposes an intelligent reflecting surface (IRS)-enabled radar stealth mechanism. The method dynamically manipulates channel phase responses via IRS to distort angle-of-arrival (AoA) estimation, while satisfying the signal-to-noise ratio (SNR) constraint of the communication link. Innovatively, the IRS-assisted radar stealth is formulated as a min-max game between the DFBS and the IRS; leveraging geometric insights, a closed-form optimal solution to the resulting non-convex optimization problem is derived. Integrating game theory, geometric optimization, and IRS phase control, the approach achieves significant AoA estimation error inflation—effectively suppressing illicit localization—while degrading communication performance by less than 1.2%.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Mixed Discrete/Continuous Search
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems

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.

Problem

• 6G Network
• Unauthorized ISAC System
• Location Privacy

Innovation

• Intelligent Surfaces
• Radar Evasion
• 6G Network