The extensive deployment of Low Earth Orbit (LEO) satellites introduces significant security challenges for communication security issues in Internet of Things (IoT) networks. With the rising number of satellites potentially acting as eavesdroppers, integrating Physical Layer Security (PLS) into satellite communications has become increasingly critical. However, these studies are facing challenges such as dealing with dynamic topology difficulties, limitations in interference analysis, and the high complexity of performance evaluation. To address these challenges, for the first time, we investigate PLS strategies in satellite communications using the Stochastic Geometry (SG) analytical framework. We consider the uplink communication scenario in an LEO-enabled IoT network, where multi-tier satellites from different operators respectively serve as legitimate receivers and eavesdroppers. In this scenario, we derive low-complexity analytical expressions for the security performance metrics, namely availability probability, successful communication probability, and secure communication probability. By introducing the power allocation parameters, we incorporate the Artificial Noise (AN) technique, which is an important PLS strategy, into this analytical framework and evaluate the gains it brings to secure transmission. In addition to the AN technique, we also analyze the impact of constellation configuration, physical layer parameters, and network layer parameters on the aforementioned metrics.

翻译：低地球轨道（LEO）卫星的大规模部署给物联网（IoT）网络的通信安全问题带来了重大的安全挑战。随着可能充当窃听者的卫星数量不断增加，将物理层安全（PLS）技术集成到卫星通信中变得日益关键。然而，现有研究面临着诸多挑战，例如处理动态拓扑的困难、干扰分析的局限性以及性能评估的高复杂度。为应对这些挑战，我们首次利用随机几何（SG）分析框架来研究卫星通信中的物理层安全策略。我们考虑一个由低轨卫星支持的物联网网络中的上行链路通信场景，其中来自不同运营商的多层卫星分别充当合法接收者和窃听者。在此场景下，我们推导了安全性能指标（即可用概率、成功通信概率和安全通信概率）的低复杂度解析表达式。通过引入功率分配参数，我们将人工噪声（AN）技术——一种重要的物理层安全策略——纳入此分析框架，并评估了其为安全传输带来的增益。除了人工噪声技术外，我们还分析了星座配置、物理层参数以及网络层参数对上述性能指标的影响。