# Risk Assessment of UAV Cyber Range Based on Bayesian-Nash Equilibrium
## 6 Application and Analysis
\begin{table}
\begin{tabular}{l l l l l} \hline \hline \multirow{2}{*}{**Classification**} & \multirow{2}{*}{**Base Attack**} & \multirow{2}{*}{**Description**} & \multicolumn{2}{c}{**Adventurous Attacker**} & \multicolumn{2}{c}{**Conservative Attacker**} \\ \cline{4-5}  & & & \(b_{1}^{A}\) & \(b_{2}^{A}\) & \(b_{3}^{A}\) & \(b_{4}^{A}\) \\ \hline \multirow{4}{*}{Data} & \(a_{7}\) & Stealing flight logs and mission & & \\ \cline{2-5}  & Theft of sensitive data & data from unmanned & \(\blacksquare\) & & \\ \cline{1-1} \cline{2-5}  & \(a_{8}\) & Access control systems through & & \\ \cline{1-1} \cline{2-5}  & Control system & malware to hijack flight control & & \(\blacksquare\) \\ \cline{1-1} \cline{2-5}  & hijacking & of UAV & & & \\ \hline \multirow{4}{*}{DoS} & \(a_{9}\) & A UDP flood attack disables the & & & \\ \cline{1-1} \cline{2-5}  & Launch a DoS attack & UAV’s communication system & & & \\ \cline{1-1} \cline{2-5}  & & If the attacker is able to gain & & \\ \cline{1-1} \cline{2-5}  & \(a_{10}\) & sufficient access, it may send a & & \\ \cline{1-1} \cline{2-5}  & Physical failure & self-destruct command or directly & & \(\blacksquare\) & \\ \cline{1-1} \cline{2-5}  & & operate the UAV to perform & & \\ \cline{1-1} \cline{2-5}  & physical damage & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._  
that is, the attack income of the attacker is not necessarily equal to the economic loss caused by the defender, which should be analyzed according to the specific situation. In fact, if the benefit of the attack is greater than the financial loss of the defender, this is the preferred effect of the attacker. Therefore, based on this consideration, in the calculation example analysis in this section, the \(ALE\) value and \(G\) value in the table are set to be equal and the latter is greater than the former so as to carry out a more comprehensive data analysis. After determining the strategy set of the participants and obtaining the basic data of the attack-defense tree model, the proposed method is applied to establish the game model and solve the Nash equilibrium so as to deduce the strategy choice preferences of the attacker and the defender considering the capital cost and economic benefit. The formula in Section 3 is used to calculate the strategic gains of the participants, and the prior probability of the defenders against the types of attackers is obtained by combining the analysis of the attack history and defense history of the UAV cyber range: (adventurous attacker, conservative attacker) = (0.55, 0.45); the prior probability of the attacker on the type of defender: (high level defender, low level defender) = (0.6, 0.4). The mixed strategy Bayesian-Nash equilibrium is calculated by the equilibrium formula, and the calculation results are shown in Table 11.  
According to the analysis of the actual situation, in the defense process of the UAV range, the defender's strategy is determined. Therefore, assuming that the defender adopts the defense strategy \(b_{1}^{D}\) at this time, according to the calculated security risk value \(R_{i}\), we can obtain:  
\[R_{i}=\sum_{l_{2}=1}^{2}P(t_{A}|t_{D})\sum_{i_{1}=1}^{2}f_{l_{2}}^{A^{*}}(t_{A })\frac{U_{D}(b_{A},b_{D},t_{D})}{U_{D}^{\max}(b_{A},b_{D},t_{D})}=0.648 \tag{11}\]  
The unmanned aerial vehicle's navigation and control system, communication system and mission payload system are important subsystems in UAV range. This paper considers the impact of subsystem security risk on the overall threat of the UAV cyber range. Taking three subsystems as an example, the calculated security risk value of each subsystem is (R1, R2, R3) = (0.648, 0.591, 0.759). According to the importance evaluation of the three subsystems in the UAV cyber range by experts, the weight vector of the subsystem is calculated by using the fuzzy Analytic Hierarchy Process as (W1, W2, W3) = (0.528, 0.309, 0.261).