## 4 Experimental Results and Discussion
### Network Centrality Metrics
Finally, in \(tv_{123\_LEO}\), \(GW_{1}\) showed the highest betweenness centrality, followed by the \(RT\). The application of the protocol patch and both patches significantly \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{6}{l}{**(a) Targeting the space segment**} \\ \hline \multirow{2}{*}{**\
\begin{tabular}{c} **Threat** \\ **Vector** \\ \end{tabular}} & \multirow{2}{*}{**Node**} & \multicolumn{6}{c}{**Degree Centrality**} \\ \cline{3-8}  & & & **No Patch** & **OS Patch** & **Protocol** & **Both** & **Bot** & **CFR** & **Average** \\ \hline \multirow{6}{*}{\(tv_{13}\)} & \(FW\) & 2 & 1 & 2 & 1 & 2 & 1.6 \\  & \(RT\) & 4 & 3 & 3 & 2 & 4 & 3.2 \\ \cline{1-1}  & \(GCS\) & 3 & 3 & 3 & 2 & 2 & 2.6 \\ \cline{1-1}  & \(GW_{1}\) & 3 & 3 & 2 & 2 & 2 & 2.4 \\ \cline{1-1}  & \(GW_{2}\) & 2 & 2 & 1 & 1 & 1 & 1.4 \\ \hline \multirow{6}{*}{\(tv_{23}\)} & \(UAV\) & 2 & 1 & 2 & 1 & 2 & 1.6 \\ \cline{1-1}  & \(IoT\) & 3 & 2 & 3 & 1 & 3 & 2.4 \\ \cline{1-1}  & \(GW_{1}\) & 3 & 3 & 1 & 1 & 1 & 1.8 \\ \cline{1-1}  & \(GW_{2}\) & 3 & 3 & 2 & 2 & 2 & 2.4 \\ \hline \multicolumn{6}{l}{**(b) Originating in the space segment**} \\ \hline \hline \multirow{2}{*}{
\begin{tabular}{c} **Threat** \\ **Vector** \\ \end{tabular} } & \multirow{2}{*}{**Node**} & \multicolumn{6}{c}{**Degree Centrality**} \\ \cline{3-8}  & & & **No Patch** & **OS Patch** & **Protocol** & **Both** & **Bot** & **CFR** & **Average** \\ \hline \multirow{6}{*}{\(tv_{123\_MEO}\)} & \(MEO\) & 3 & 3 & 1 & 1 & 3 & 2.2 \\  & \(GCS\) & 2 & 2 & 2 & 2 & 2 & 2.0 \\ \cline{1-1} \cline{2-8}  & \(RT\) & 3 & 2 & 2 & 2 & 3 & 2.0 \\ \cline{1-1}  & \(GW_{1}\) & 3 & 3 & 2 & 1 & 2 & 2.2 \\ \cline{1-1}  & \(GW_{2}\) & 3 & 3 & 2 & 1 & 2 & 2.2 \\ \hline \multirow{6}{*}{\(tv_{123\_LEO}\)} & \(LEO\) & 4 & 4 & 3 & 3 & 4 & 3.6 \\ \cline{1-1}  & \(GCS\) & 2 & 2 & 2 & 2 & 2.0 \\ \cline{1-1} \cline{2-8}  & \(RT\) & 3 & 2 & 3 & 2 & 3 & 2.6 \\ \cline{1-1}  & \(GW_{1}\) & 5 & 5 & 4 & 2 & 4 & 4.0 \\ \cline{1-1}  & \(GW_{2}\) & 4 & 4 & 3 & 2 & 3 & 3.2 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Security assessment using the degree centrality metric. decreased \(GW_{1}\)'s betweenness centrality, preventing specific nodes from becoming major attack paths within the network. Through this analysis, we were able to quantitatively assess the impacts of specific nodes on the data flow within the satellite network and evaluate the effectiveness of each patch strategy with respect to the security posture. In particular, the application of both patches or CFR emerged as the most effective method for restricting attack paths and optimizing the traffic flow. The application of both patches decreased the betweenness centralities of the key nodes, leading to a more balanced distribution of the data flow within the network. The application of CFR played a crucial role in dispersing traffic across the key intermediary nodes, helping to mitigate the risk of specific nodes becoming concentrated attack surfaces. The protocol patch effectively reduced the betweenness centralities of specific nodes in the user segment, preventing threat vectors from focusing on particular nodes. This analysis confirmed that a multipatch strategy is the most effective way to enhance the satellite network security.