## 2 Traditional Encryption Techniques
### Theoretical Models and the Influence of Environmental Factors  
Theoretical models and simulations are used to evaluate the effect of dynamic channel conditions on encryption performance. Signal attenuation models based on electromagnetic wave propagation equations in the atmosphere allow the estimation of decreases in the signal power with distance, which can lead to transmission errors and reduced safety [13]. In particular, the attenuation model can be represented as follows:  
\[\mathrm{L}=20\mathrm{log}_{10}(4\pi\mathrm{d}/\lambda)+\gamma\mathrm{d}. \tag{1}\]  
Delay models considering the distance between UAVs and ground stations as well as the signal propagation rate illustrate the impact of the data transmission time on the performance of encryption algorithms, especially asymmetric ones that require more computation time [14]. The theoretical attenuation and delay models were validated through simulations using UAV-specific parameters, such as varying altitudes and operational velocities. The results showed a deviation of less than 5% between the theoretical predictions and simulated data, confirming the models' reliability for LEO conditions. The delay can be calculated by the following formula:  
\[\mathrm{D}=\mathrm{d}/\mathrm{c}, \tag{2}\]  
where:  
\(\mathrm{D}\) is the delay in seconds  
\(\mathrm{d}\) is the distance between the transmitter and the receiver  
\(\mathrm{c}\) is the speed of light  
The environmental conditions characteristic of communications in low Earth orbit, such as signal attenuation, Doppler effects, and atmospheric interference, can also affect the reliability and speed of traditional encryption methods. Atmospheric signal attenuation, due to the absorption and scattering of electromagnetic waves, can cause packet loss and reduce data rates. Doppler effects due to the relative motion of the UAV and the ground station can cause frequency shifts, making synchronization between the sender and \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Threat** & \begin{tabular}{c} **Vulnerable** \\ **Algorithm (s)** \\ \end{tabular} & **Impact** & **Mitigation** & **Challenges** \\ \hline Brute Force & & \begin{tabular}{c} Reduced \\ security, faster \\ key breaking via \\ quantum \\ \end{tabular} & \begin{tabular}{c} Use longer keys, \\ quantum- \\ resistant \\ algorithms \\ \end{tabular} & \begin{tabular}{c} High resource \\ demands \\ on UAVs \\ \end{tabular} \\ \hline Third-Channel & \multirow{3}{*}{RSA} & Private key exposure via & \begin{tabular}{c} Physically \\ unclonable \\ functions (PUFs) \\ \end{tabular} & \begin{tabular}{c} Increased power \\ usage, reduced \\ flight time \\ \end{tabular} \\ \hline Data & \multirow{3}{*}{AES, RSA} & Data tampering, misclassification, delays & \begin{tabular}{c} Stronger \\ encryption, error \\ detection, \\ adaptive \\ methods \\ \end{tabular} & \begin{tabular}{c} Environmental \\ factors disrupt \\ signal integrity \\ \end{tabular} \\ \hline Environmental & \multirow{3}{*}{AES, RSA} & \begin{tabular}{c} Compromised \\ encryption due \\ to mo- \\ tion/temperature \\ \end{tabular} & \
\begin{tabular}{c} Adaptive \\ encryption \\ based on \\ conditions \\ \end{tabular} &
\begin{tabular}{c} Complex \\ adaptation to \\ changing \\ environments \\ \end{tabular} \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Comparison of Threats, vulnerable algorithms, impacts, mitigation strategies, and challenges in UAV encryption systems. receiver difficult [15]. Doppler compensation strategies such as real-time beam steering and adaptive frequency shifting have been shown to reduce synchronization errors by 20-30% in UAV systems operating at speeds exceeding 100 km/h, maintaining the encryption stability in dynamic LEO environments. Atmospheric interference such as rain, snow, or fog can cause transmission errors, which can compromise the integrity of encrypted data.