In this paper, we present a signaling design for secure integrated sensing and communication (ISAC) systems comprising a dual-functional multi-input multi-output (MIMO) base station (BS) that simultaneously communicates with multiple users while detecting targets present in their vicinity, which are regarded as potential eavesdroppers. In particular, assuming that the distribution of each parameter to be estimated is known \textit{a priori}, we focus on optimizing the targets' sensing performance. To this end, we derive and minimize the Bayesian Cram\'er-Rao bound (BCRB), while ensuring certain communication quality of service (QoS) by exploiting constructive interference (CI). The latter scheme enforces that the received signals at the eavesdropping targets fall into the destructive region of the signal constellation, to deteriorate their decoding probability, thus enhancing the ISAC's system physical-layer security (PLS) capability. To tackle the nonconvexity of the formulated problem, a tailored successive convex approximation method is proposed for its efficient solution. Our extensive numerical results verify the effectiveness of the proposed secure ISAC design showing that the proposed algorithm outperforms block-level precoding techniques.

翻译：本文针对安全型集成感知与通信（ISAC）系统提出一种信号设计方法。该系统包含一个双功能多输入多输出（MIMO）基站（BS），可在检测周围潜在窃听目标的同时与多个用户进行通信。特别地，在假设待估参数先验分布已知的条件下，我们着重优化目标的感知性能。为此，通过利用构造性干扰（CI）技术，在保证通信服务质量（QoS）的前提下推导并最小化贝叶斯克拉美-罗界（BCRB）。该方案通过强制窃听目标接收信号落入信号星座图的破坏性区域，降低其解码概率，从而增强ISAC系统的物理层安全（PLS）能力。针对所构建问题的非凸性，我们提出了一种定制化的逐次凸近似方法进行高效求解。大量数值结果验证了所提安全ISAC设计的有效性，表明所提算法优于块级预编码技术。