# Hybrid Trust Model for Node-Centric Misbehavior Detection in Dynamic Behavior-Homogeneous Clusters
## 8 Performance Analysis
### Experiment 1: Total Trust Value Assessment at the Vehicle Node Layer
Performance Differences of the Mixed Trust Model Under Different Densities  
To explore the performance differences of the hybrid trust model in scenarios with varying densities, the experiment statistically analyzed the proportion of alerted vehicles in low, medium, and high-density scenarios, as shown in Figure 10. In high-density scenarios, the number of alerted vehicles is generally higher than in medium and low-density scenarios. This is mainly attributed to the high penetration rate of vehicular network messages in high-density scenarios, achieving almost full coverage. However, message conflicts in high-density vehicular networks may lead to data loss. Therefore, in some cases, the number of alerted vehicles in medium-density scenarios may be higher than in high-density scenarios. 2. Impact of Information Interaction on Total Trust Value of Vehicles in Different Traffic Densities  
To more clearly demonstrate the impact of information interaction on vehicle trustworthiness, the experiment set a hypothesis: in both low- and high-density scenarios, vehicles are considered trustworthy. Then, the experiment explored the impact of successful and failed information interactions on vehicle trustworthiness in these two scenarios. The results are shown in Figures 11 and 12. It is important to note that the calculation of a vehicle's trust value depends on information transmission between vehicles and feedback from other vehicles. In low-density traffic scenarios, failed information interactions may  
Figure 10: Alerted vehicles in different density scenarios. lead to insufficient trust data, making the impact of failed interactions on trust calculation more significant in low-density scenarios than in high-density scenarios. From Figure 12, it can be observed that in high-density scenarios, even if the number of failed information interactions falls within a certain range, the trustworthiness of credible vehicles in the current scenario can still be judged to be higher than 0.5, indicating they are trustworthy. Experiment 3: Calculation of Average Total Trust Value and Vehicle Status Determination Based on Vehicle Cluster Trust Threshold  
1) Vehicle Status Determination Based on Trust Threshold Following the Method  
The cluster head is responsible for collecting vehicle behavior information within its wireless communication range. In the simulation experiment, we selected 5 vehicles from a database of a vehicle cluster consisting of 20 vehicles. The behavior of these five vehicles was evaluated using the trust model, and their average total trust values were calculated. The experiment results are shown in Table 3.  
Figure 11: The impact of information interaction on the average trust value of vehicles at a traffic density of 0.25. Figure 12: The impact of information interaction on the average trust value of vehicles at a traffic density of 0.35. \begin{table}
\begin{tabular}{c c c c c} \hline
**Vehicle ID** & **Time** & **Average Total Trust Value** & **Average Weight of Node Relationship** & **Vehicle Status** \\ \hline
1 & 7 & 0.718 & 0.977 & Trusted \\
3 & 7 & 0.788 & 0.948 & Trusted \\
7 & 7 & 0.553 & 0.957 & Neutral \\
13 & 7 & 0.371 & 0.771 & Misbehavior \\
17 & 7 & 0.509 & 0.955 & Neutral \\ \hline \end{tabular}
\end{table} 
Table 3: Average total trust values collected by the cluster head. In the vehicle cluster \(C_{2}\), the average total trust value of all vehicles is 0.752, which sets the range \([0.376,0.752]\) for the cluster head to determine misbehavior vehicle nodes. Based on this, vehicle \(V_{3}\) is determined as trustworthy, \(V_{13}\) as malicious, and \(V_{1}\), \(V_{7}\) and \(V_{17}\) as vehicles requiring periodic checks. According to the time calculations for periodic checks, the check times for \(V_{1}\), \(V_{7}\) and \(V_{17}\) are, respectively, 13.85 s, 79.60 s, and 97.14 s. After the check period, if their average total trust value is higher than the cluster's average, they are deemed trustworthy; otherwise, they are considered malicious nodes.