Satellite communication networks operate under stringent computational constraints and are susceptible to sophisticated cyberattacks. This paper introduces a novel defense framework that decouples security optimization into ground-based analysis and onboard real-time execution. In the long-term loop, the ground segment processes historical data to estimate key statistical parameters of the task environment. Additionally, we incorporate the time-varying characteristics of satellite wireless links to account for the dynamic communication context. In the short-term loop, the satellite employs a receding horizon optimization that models dynamic task arrivals and maximizes a utility function considering detection rates and resource costs. To counter intelligent adversaries interception, we introduce a deception mechanism using Bayesian persuasion theory. By strategically manipulating the short-term action sequences in the telemetry downlink, we mislead an external attacker's beliefs. We mathematically model the attacker's optimal response under channel uncertainty and demonstrate that our framework significantly reduces attacker utility. The approach's effectiveness is formally proven using Lyapunov theory.

翻译：卫星通信网络在严格的计算约束下运行，且易受复杂网络攻击。本文提出一种新颖的防御框架，将安全优化解耦为地面分析与星上实时执行。在长期循环中，地面段处理历史数据以估计任务环境的关键统计参数。此外，我们结合卫星无线链路的时变特性来适应动态通信环境。在短期循环中，卫星采用滚动时域优化方法，对动态任务到达进行建模，并最大化考虑检测率与资源成本的效用函数。为应对智能对手的拦截，我们引入基于贝叶斯劝说理论的欺骗机制。通过策略性地操控遥测下行链路的短期动作序列，我们误导外部攻击者的信念。我们在信道不确定性下对攻击者的最优响应进行数学建模，并证明该框架能显著降低攻击者效用。该方法的有效性通过李雅普诺夫理论得到严格证明。