# Satellite Network Security Routing Technology Based on Deep Learning and Trust Management
## 4 Experimental Simulation and Analysis
### Analysis of Results
#### 4.2.2 Packet Loss Rate  
The packet loss rate refers to the ratio of the number of packets lost in the process of data transmission to the number of packets sent. As can be seen from the figure below, when there are no malicious nodes in the satellite network, the packet loss rates of the ACO algorithm, TAODV algorithm, SLT algorithm, and TVAE algorithm are not much different. At this point, packet loss may occur due to normal factors such as network topology changes, or it may be caused by queue congestion. As the proportion of malicious nodes in the network increases gradually, the packet loss rate of each algorithm also increases. Because the ACO algorithm does not consider security factors, it is unable to cope with malicious node attacks. Malicious nodes usually launch behaviors such as black hole attacks to discard packets, or for selfish attacks to discard certain specific packets. These attacks will cause the packet loss rate of the algorithm to rise sharply, seriously affecting the normal communication of data. Therefore, the packet loss rate of the ACO algorithm can be seen in the figure with a large increase. When the number of malicious nodes increases to 14, the packet loss rate exceeds 50%. At this time, the algorithm is already in a functional failure state, and the network built by it cannot carry out data communication. However, the other three algorithms use the trust model to harden their routing algorithms, so they can avoid malicious nodes as much as possible in the routing process, to reduce the damage of malicious nodes to the satellite network. Therefore, the packet loss rate increases slightly when the number of malicious nodes increases. When four malicious nodes begin to appear in the network, the packet loss rate of the SLT algorithm and TVAE algorithm is almost 5%, the packet loss rate of the TAODV algorithm is 11%, and the packet loss rate of the ACO algorithm has reached 18%. Later, with the increase of malicious nodes, when malicious nodes reach 16, the packet loss rate of the TAODV algorithm is 28%, the packet loss rate of the SLT algorithm is 18%, and the packet loss rate of the TVAE algorithm is 12%. The above results show that the TAODV algorithm, SLT algorithm, and TVAE algorithm all have a certain ability to resist malicious nodes in the network, so the packet loss rate of these three algorithms shows the same trend with the increase of the number of malicious nodes. However, since the TVAE algorithm adopts a novel neural network to detect malicious nodes, it can identify malicious nodes well and guide ant colonies to actively avoid these harmful nodes in the process of pathfinding in advance, so the possibility of being attacked is minimized. Therefore, its packet loss rate can be stabilized in a small range with the increase of malicious nodes. Furthermore, as depicted in Figure 7, the four curves exhibit separation and no longer intersect as the number of malicious nodes increases. In terms of the overall trend, with a greater number of malicious nodes, the ACO algorithm's curve experiences a larger upward incline, while the curves of the other three algorithms rise more gradually. The reasons behind these outcomes are as follows:  
The ACO algorithm lacks a security trust model to reinforce the security of its routing, which positions its curve at the top of Figure 7. The TAODV algorithm, due to its utilization of a trust model belonging to traditional mathematical models, demonstrates limited effectiveness against malicious attacks and cannot match the capabilities of the SLT and TVAE algorithms. Additionally, although the trust model of the SLT algorithm also employs traditional mathematical models, the algorithm itself is equipped with a fault detection mechanism, providing supplementary assistance to the trust model in combating malicious attacks. The TVAE algorithm adopts an intelligent security trust model, allowing it to effectively bypass malicious nodes when facing malicious attacks.