## 5 Simulations and Discussions
### Evaluation of Detection Capability  
The generation mechanism of SH and GH nodes caused by SDC errors has been given in Section 3. This paper proposes SH and GH nodes induced by SDC errors and the detection method based on DT and routing process files for the first time. There are few detection methods and data sets for SH and GH nodes caused by SDC errors. The existing SH or GH detection methods are based on node behavior or network traffic, such as RFTrust [17], SoS-RPL [18], and CEBD [6]. Whether caused by SDC or not, the behavior of SH or GH nodes during the forwarding phase is consistent (such as dropping data packages). That is, SH (or GH) nodes caused by SDC behave in the same way as SH (or GH) nodes caused in other ways. Therefore, from the perspective of detection capabilities, the proposed method and existing SH or GH detection methods are comparable. We construct a data set based on the satellite network scenario described in Section 5.1 to evaluate the performance and overhead of the proposed method. The data set contains 100 cases with SH nodes, 100 cases with GH nodes, 100 normal cases, and 100 other cases. We obtained the detection results of existing methods by setting SH or GH nodes and simulating communication between nodes in the ONE simulator and compared them with the proposed method. Existing detection methods for SH and GH nodes are mainly based on traffic. This method usually detects the network traffic when the satellite network carries out the actual packet forwarding after the route update is completed. In contrast, the method proposed in this paper can detect the intermediate files in the process of satellite network route update and can find the SH and GH nodes faster and timelier. In addition, if the packet does not pass through the SH or GH nodes during packet forwarding, traffic-based detection methods cannot effectively detect the fault node. Unlike existing methods, the proposed method can logically detect SH and GH nodes caused by SDC errors by obtaining the position information, link information, routing information base, routing table, and other routing update process files of satellite nodes, thus improving the reliability and availability of satellite networks. To evaluate whether there are False Negatives (FNs) or False Positives (FPs) in this method, we recorded the experiment results and calculated the accuracy, precision, and recall rate of the results. In this example, a sample with SH/GH nodes is defined as a positive sample, and a sample without SH/GH nodes is defined as a negative sample. The definition of relevant concepts is as follows:  
* TP (True Positive): During GH/SH detection, the detection algorithm detects positive samples as positive samples;
* TN (True Negative): During GH/SH detection, the detection algorithm detects negative samples as negative samples;
* FN (False Negative): During GH/SH detection, the detection algorithm detects positive samples as negative samples, that is, the model fails to identify that the sample has a GH/SH node;
* FP (False Positive): During GH/SH detection, the detection algorithm detects negative samples as positive samples, that is, the model misreports that the sample has a GH/SH node;* Accuracy: ac = TP + TN/(TP + TN + FP + FN);
* Precision: pr = TP/(TP + FP);
* Recall: re = TP/(TP + FN). (1) Evaluation of SH detection capability  
We select 300 RIBs from the data set, which include 100 cases with SH, 100 normal cases, and 100 cases with link loss or weight change, to evaluate the accuracy of the proposed SH detection algorithm. The confusion matrix of the results is shown in Table 6. We also compare the proposed method with the following SH detection methods:  
* RFTrust [17] considers packet delivery ratio, average delay, and energy consumption, and uses Random Forest and subjective logic to detect SHs. * SoS-RPL [18] defines two features (DI-RANK and DV-RANK) to detect SHs, and features can be updated by exchanging routing graph information. * INTI [33] estimates the reputation of the node to detect SH attacks.