## 1 Introduction  
According to data from the National Oceanic and Atmospheric Administration (NOAA) Space Environmental Service Center, single-event upset (SEU) events caused by high-energy particles occur every year on average [1]. SEU refers to the reaction caused by a single high-energy particle entering the sensitive area of semiconductor devices (such as microprocessors, semiconductor memories, or power transistors), resulting in a single-bit upset of memory cells [2]. In the complex space environment, cosmic rays or high-energy particles can cause SEU in satellite systems and cause errors in program outputs. Silent Data Corruption (SDC) is a type of SEU error that is hard to detect [3]. SDC errors in satellite routing programs may spread to the satellite network during the routing update process, causing the satellite network to be subject to various threats. Among them, Sinkhole (SH) and Grayhole (GH) nodes are among the most serious threats in the network layer. In this study, we find that in the route discovery phase, a satellite affected by SDC errors may claim to have a false inter-satellite link, and the data packets passing through the link will be discarded, resulting in a SH node. In the routing planning stage, SEU may cause data loss, destination node change, and next hop node change in the routing table, which will make the affected satellite unable to find the next hop and discard the data packets, thus generating a GH node. In this paper, we regard the nodes that discard all packets passing through themselves (Blackhole nodes) as a special case of GH nodes. Digital twins (DTs) are virtual reflections of physical objects, which can make full use of the physical model, sensor update data, history data, and other information to map the real physical object in the virtual digital space [4]. The combination of digital twins and satellite networks is still in the exploration stage. The US Air Force has used a digital twin of the Lockheed Martin GPS IIR satellite to detect cybersecurity issues by performing penetration testing on the digital replica of the satellite. The satellite network topology is time-varying, and the satellite movement in orbit is predictable [5]. Therefore, most satellite network routing update mechanisms consist of two main stages: the route discovery phase and the route planning phase. Network threats have always been a research hotspot. The existing attack detection methods are mainly based on machine learning [6; 7] and rules [8; 9]. However, as shown in Figure 1, most of the above methods detect the traffic during the satellites' data forwarding process, after the routing update, and cannot effectively detect the fault node when the traffic does not pass through the problem node [10]. The proposed method works at the routing update stage. By dividing the routing update process into a route discovery phase and a route planning phase, a routing information base (RIB) generated during the route discovery phase could be completed before data forwarding, and the detection of routing tables may be completed before the satellite queries the routing table (data forwarding stage). For SHs and GHs induced by SDC errors, it is worthwhile to design a detection and protection framework that could complete the detection as soon as possible and occupy a small amount of satellite computing resources. The main challenges facing any detection and protection technology of SH and GH nodes induced by SDC errors are: (1) SHs and GHs are relatively serious threats on the network layer, and current research mainly focuses on SHs and GHs caused by malicious nodes. SEU can cause SDC errors in the satellite network routing programs, and further cause SHs and GHs. At present, few studies analyze the generation mechanism of the SH and GH nodes induced by SDC errors. (2) The existing research determines whether SH nodes and GH nodes exist in the satellite network by establishing a model based on rules or machine learning and analyzing the forwarding behavior or traffic of the satellites.