## 4 Experimental Results and Discussion
### Vulnerability Score Metric  
In this study, we utilized the vulnerability score to evaluate the security states of satellite networks quantitatively. From this, we derived seven key metrics from attack scenarios for each threat vector and conducted an analysis. No. of paths indicates the number of attack paths available for an attacker to reach the target in a given model. A higher value implies a more significant number of potential attack possibilities. The shortest path length represents the length of the shortest attack path that an attacker must take to reach the target. Shorter paths suggest a higher likelihood of network vulnerability. The mean path length refers to the \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline \multicolumn{2}{c}{**(a) Targeting the space segment**} & \multicolumn{6}{c}{**Betweenness Centrality**} \\ \hline \multirow{2}{*}{\begin{tabular}{c} **Threat** \\ **Vector** \\ \end{tabular} } & \multirow{2}{*}{**Node**} & \multirow{2}{*}{**No Patch**} & \multirow{2}{*}{**OS Patch**} & \multirow{2}{*}{\
\begin{tabular}{c} **Protocol** \\ **Patch** \\ \end{tabular} } & \multirow{2}{*}{**Both**} & \multirow{2}{*}{**CFR**} & \multirow{2}{*}{**Average**} \\  & & & & & & & \\ \hline \multirow{6}{*}{\(tv_{123\text{-}ACO}\)} & _FW_ & 0.14 & 0.17 & 0.25 & 0.25 & 0.25 & 0.21 \\  & _RT_ & 0.36 & 0.33 & 0.25 & 0.17 & 0.17 & 0.26 \\  & _GCS_ & 0.21 & 0.25 & 0.33 & 0.42 & 0.42 & 0.33 \\  & \(GW_{1}\) & 0.14 & 0.17 & 0.08 & 0.08 & 0.08 & 0.11 \\  & \(GW_{2}\) & 0.14 & 0.08 & 0.08 & 0.08 & 0.08 & 0.10 \\ \hline \multirow{6}{*}{\(tv_{23}\)} & _UAV_ & 0.14 & 0.10 & 0.14 & 0.07 & 0.10 & 0.11 \\  & _IoT_ & 0.29 & 0.20 & 0.29 & 0.13 & 0.20 & 0.22 \\ \cline{1-1}  & \(GW_{1}\) & 0.19 & 0.17 & 0.10 & 0.05 & 0.10 & 0.12 \\ \cline{1-1}  & \(GW_{2}\) & 0.19 & 0.17 & 0.14 & 0.14 & 0.15 & 0.15 \\ \hline \hline \multicolumn{2}{c}{**(b) Initiated in the space segment**} & \multicolumn{6}{c}{**Betweenness Centrality**} \\ \hline \multirow{2}{*}{
\begin{tabular}{c} **Threat** \\ **Vector** \\ \end{tabular} } & \multirow{2}{*}{**Node**} & \multirow{2}{*}{**No Patch**} & \multirow{2}{*}{**OS Patch**} & \multirow{2}{*}{**Protocol**} & \multirow{2}{*}{**Both**} & \multirow{2}{*}{**Patches**} & \multirow{2}{*}{**CFR**} & \multirow{2}{*}{**Average**} \\  & & & & & & & \\ \hline \multirow{6}{*}{\(tv_{123\text{-}ACO}\)} & _MEO_ & 0.21 & 0.17 & 0.25 & 0.25 & 0.21 & 0.22 \\  & _GCS_ & 0.36 & 0.33 & 0.25 & 0.25 & 0.36 & 0.29 \\ \cline{1-1}  & _RT_ & 0.43 & 0.42 & 0.33 & 0.25 & 0.43 & 0.37 \\ \cline{1-1}  & \(GW_{1}\) & 0.21 & 0.25 & 0.08 & 0.08 & 0.21 & 0.17 \\ \cline{1-1}  & \(GW_{2}\) & 0.21 & 0.17 & 0.08 & 0.08 & 0.21 & 0.15 \\ \hline \multirow{6}{*}{\(tv_{123\text{-}ACO}\)} & _LEO_ & 0.36 & 0.36 & 0.25 & 0.17 & 0.36 & 0.32 \\ \cline{1-1}  & _GCS_ & 0.21 & 0.21 & 0.17 & 0.17 & 0.21 & 0.20 \\ \cline{1-1} \cline{1-1}  & \(RT\) & 0.43 & 0.33 & 0.33 & 0.25 & 0.43 & 0.37 \\ \cline{1-1}  & \(GW_{1}\) & 0.50 & 0.50 & 0.42 & 0.17 & 0.42 & 0.40 \\ \cline{1-1}  & \(GW_{2}\) & 0.43 & 0.43 & 0.33 & 0.17 & 0.33 & 0.34 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Security assessment using the betweenness centrality metric. average length of all the attack paths within the model and is used to assess the overall security level of the network. The max probability is the value of the attack path with the highest success rate. This indicates the most vulnerable point in the network for the attacker. The total probability is the sum of all the attack path success probabilities, calculated using the logical sum method. It provides a comprehensive evaluation of the likelihood of an attack succeeding within the network. The max risk refers to the value of the attack path with the highest risk. It helps to identify the specific nodes or paths the most exposed to security threats. The total risk is the sum of the values of all the attack paths, serving as a metric for evaluating the overall security threat level of the network.