Title: Sensing-Secure ISAC: Ambiguity Function Engineering for Impairing Unauthorized Sensing Show Chinese title

Title: 感知安全的ISAC：破坏未经授权感知的模糊函数设计

Abstract: The deployment of integrated sensing and communication (ISAC) brings along unprecedented vulnerabilities to authorized sensing, necessitating the development of secure solutions. Sensing parameters are embedded within the target-reflected signal leaked to unauthorized passive radar sensing eavesdroppers (Eve), implying that they can silently extract sensory information without prior knowledge of the information data. To overcome this limitation, we propose a sensing-secure ISAC framework that ensures secure target detection and estimation for the legitimate system, while obfuscating unauthorized sensing without requiring any prior knowledge of Eve. By introducing artificial imperfections into the ambiguity function (AF) of ISAC signals, we introduce artificial targets into Eve's range profile which increase its range estimation ambiguity. In contrast, the legitimate sensing receiver (Alice) can suppress these AF artifacts using mismatched filtering, albeit at the expense of signal-to-noise ratio (SNR) loss. Employing an OFDM signal, a structured subcarrier power allocation scheme is designed to shape the secure autocorrelation function (ACF), inserting periodic peaks to mislead Eve's range estimation and degrade target detection performance. To quantify the sensing security, we introduce peak sidelobe level (PSL) and integrated sidelobe level (ISL) as key performance metrics. Then, we analyze the three-way trade-offs between communication, legitimate sensing, and sensing security, highlighting the impact of the proposed sensing-secure ISAC signaling on system performance. We formulate a convex optimization problem to maximize ISAC performance while guaranteeing a certain sensing security level. Numerical results validate the effectiveness of the proposed sensing-secure ISAC signaling, demonstrating its ability to degrade Eve's target estimation while preserving Alice's performance. Show Chinese abstract

Abstract: 集成感知与通信（ISAC）的部署给授权感知带来了前所未有的漏洞，需要开发安全的解决方案。 感知参数嵌入到被未经授权的被动雷达感知窃听者（Eve）泄露的目标反射信号中，这意味着它们可以在不事先了解信息数据的情况下静默地提取感知信息。 为克服这一限制，我们提出了一种感知安全的ISAC框架，该框架确保合法系统的安全目标检测和估计，同时在不需要任何关于Eve的先验知识的情况下混淆未经授权的感知。 通过在ISAC信号的模糊函数（AF）中引入人工缺陷，我们在Eve的范围剖面中引入了人工目标，增加了其范围估计的模糊性。 相反，合法的感知接收器（Alice）可以使用失配滤波来抑制这些AF伪影，尽管会付出信噪比（SNR）损失的代价。 采用正交频分复用（OFDM）信号，设计了一种结构化的子载波功率分配方案，以塑造安全自相关函数（ACF），插入周期性峰值以误导Eve的范围估计并降低目标检测性能。 为了量化感知安全性，我们引入了峰值旁瓣电平（PSL）和积分旁瓣电平（ISL）作为关键性能指标。 然后，我们分析了通信、合法感知和感知安全性之间的三重权衡，强调了所提出的感知安全ISAC信号对系统性能的影响。 我们制定了一个凸优化问题，在保证一定感知安全水平的同时最大化ISAC性能。 数值结果验证了所提出的感知安全ISAC信号的有效性，展示了其在降低Eve的目标估计能力的同时保持Alice性能的能力。