## 2 Related Work  
A number of research studies have applied digital twin technology to the design of satellite network protection frameworks and methods. For satellite security monitoring and verification, [PERSON] et al. [4] present a framework that combines digital twins with runtime verification and propose a state synchronization method to ensure secure and efficient long-distance communication between satellites and digital twins. To monitor the satellite's behavior in real time and ensure the reliability of the satellite systems, [PERSON] et al. [11] present a fault diagnosis and health monitoring (FD-HM) approach based on digital twins. For satellite-terrestrial networks, the satellite moving speed is faster than the ground station, which can cause inconsistent service and frequent satellite handover. To solve these problems, [PERSON] et al. [12] propose a digital-twin-assisted storage strategy for satellite-terrestrial networks (INTERLINK) and a satellite-storage-oriented handover scheme. The Iridium constellation is widely used as a satellite network simulation scenario. For example, [PERSON] et al. [13] propose an intelligent energy-aware routing protocol for satellite networks and use the Iridium constellation as an experimental scenario for performance evaluation. At the same time, some scholars try to combine digital twins with industrial facilities [14; 15; 16]. The detection of SH and GH nodes has been a hot research topic with great concern. Many detection algorithms have recently been proposed in this area. To protect the EIoT environment against SH attacks, [PERSON] et al. [8] propose an intrusion detection scheme called SAD-EIOT, in which edge servers perform SH attack detection by exchanging messages. [PERSON] et al. [17] propose a lightweight SH detection scheme FFTrust, which uses Random Forest (RF) and Subjective Logic (SL) to improve the efficiency of SH detection. [PERSON] et al. [18] propose a SH detection method SoS-RPL, which ranks the nodes in the network and allows child nodes to detect the malicious parent by using the routing graph information. Machine Learning (ML) can also be effective in detecting Blackhole attacks. [PERSON] et al. [6] constructed a behavior classifier to detect Blackhole attacks in opportunistic networks. They also designed a collusion filtering strategy to improve detection accuracy. In another study [7], three supervised ML algorithms are trained and evaluated for detecting rank and Blackhole attacks in IoT networks. At the same time, there are also studies to improve network security by strengthening routing strategies [19; 20; 21]. Considering the periodic topology changes of satellite networks, [PERSON] et al. [19] propose OPSPF, which makes use of the regularity of constellation and performs periodic routing calculations for the generation of instantaneous routing tables. In the process of routing update, the error output of the program may bring disastrous consequences to the satellite network. Therefore, there are some error detection and program protection methods [22; 23; 24]. To provide flexible and effective error protection, [PERSON] et al. [22] propose an instruction duplication error protection scheme gZDC, which can enhance protection capabilities by using coarse-grained scheduling and asymmetric control-flow signatures. [PERSON] et al. [23] propose a compiler-level redundant multithreading scheme EXPERT, which can detect the manifestation of transient and permanent faults in hardware components. By adding redundant threads, they propose a software-level triply redundant multithreading scheme FISHER [24], which can improve error detection and recovery. However, the above error detection and program protection methods do not take into account the specific characteristics of satellite networks such as latency, limited bandwidth, and constrained resources. These constraints result in such methods not being well adapted to satellite networks.