# A Self-Diagnosis Method for Detecting UAV Cyber Attacks Based on Analysis of Parameter Changes
## 3 Results and Discussion  
For the experimental study of our method, a quadcopter UAV whose architecture was developed for testing attacks and analyzing security threats was used. Table 1 presents the main characteristics of the experimental stand. One of the scenarios is that the quadcopter, having determined its current position, receives the static coordinates of its target. A copter-type UAV moves to a given point and fixes its position in space, while maintaining its altitude. In the case of an external physical impact, for example, a natural factor or impact from another object, the UAV's autopilot system increases the engine speed and sets it in the opposite direction to maintain a given position. When the UAV is displaced from its preset position, the position hold system increases the engine's RPM power depending on the distance between the preset point and the actual location of the UAV. When the UAV returns to a given point, the autopilot enters the normal altitude control mode. In the scenario of maintaining a position with fixed coordinates, an attacker could influence the direction and speed of movement. After \begin{table}
\begin{tabular}{c c} \hline \hline
**Part Name** & **Model** \\ \hline Flight controller & Pix Hawk 4 (\$Table 10.1 firmware) \\ Frame & \$5500 \\ Speed controllers & XT-XNITE 30A \\ Telemetry & \$3 DR Radio Telemetry 915 MHz 100 mW Aerial Ground Data Transmission \\  & Module for Pixhawk 4 \\ Receiver & FS-I6B \\ Battery & ZOP Power 3S 11.1V 4200 mAh 40C Lipo Battery XT60 Plug \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Experimental stand characteristics. Figure 3: The result of measuring the Kullback-Leibler divergence of the GPS noise index: (**a**) During the attack; and (**b**) under normal conditions. the start of the attack, the quadcopter navigation system perceives the broadcast signal as real, thus the actual location of the UAV differs from that determined by the navigation system. After the autopilot system detects the displacement, the UAV starts moving in the opposite direction. Thus, by indicating a fake offset on the circle, where the center will be the fixation point of the UAV, you can set the direction of movement. The attacker's task is to smoothly shift the fake geo position from the center, that is, the place where the quadcopter is fixed, to the point of the circle. By adjusting the radius of this circle, the attacker can influence the speed of the quadcopter. By adjusting the speed and motion vector, the attacker can control the location of the UAV. An important factor is that when broadcasting a fake position, the attacker must independently consider the physical impact on the UAV. To counteract external factors, it is important to determine the real position of the quadcopter. During our experimental study, an attack was carried out on the UAV five times, while the positive effect took place every time. Let us consider the data collected from the logbook during the attack and normal UAV flight. Figure 4 shows the result of fixing the UAV's flight trajectory. In Figure 4, the red line shows the estimated trajectory (Estimated) which is the flight path calculated by the on-board computer according to the accelerometer. The blue line shows the GPS trajectory (GPS projected) which is a trajectory built based on GPS module data. As we can see from Figure 3(a), both trajectories coincide during the normal flight and this indicates the normal operation of the UAV. Figure 3(b) shows that during an attack, the GPS trajectory differs from the UAV trajectory recorded by the internal sensor. Since the attack was aimed at spoofing GPS data, it led to the difference in trajectories, because many GPS systems are only updated once a second (and high-performance GNSS devices are updated five to 10 times a second) and often have an accuracy of \(\pm 1\) m only in good conditions. The condition evaluator uses other sensors to fill in the gaps between 1 s GPS updates and thus improves accuracy.