# A Self-Diagnosis Method for Detecting UAV Cyber Attacks Based on Analysis of Parameter Changes
## 1 Introduction  
A drone or Unmanned Aerial Vehicle (UAV) is a cyber-physical system combining physical processes, computation, and networking. If an attack on the Global Positioning System (GPS) is executed well, it can lead to serious consequences for a single UAV or a UAV group [1]. In addition to the natural errors and inaccuracies in sensor readings, GPS vulnerabilities also affect the flight controller. These vulnerabilities include the possibility of signal jamming or a signal distortion that disrupts the availability of the GPS signal. GPS vulnerabilities go beyond the natural properties of the transmitted signal. In GPS spoofing attacks, satellites transmitting a GPS signal are tampered with to manipulate the UAV's navigation system by transmission of fake coordinates [2, 3]. Although the GPS signal's waveform can be implemented in a secure design, thanks to authentication and encryption mechanisms [4], for military applications, civilian GPS variants, which do not have protection mechanisms, are frequently used. Consequently, civilian GPS is highly vulnerable to spoofing attacks [3]. A GPS spoofing attack entails consequences associated with the fall (crash) of the UAV or its interception and redirection along a different flight path. In both cases, these problems are related to cyber security. A targeted attack that takes control of a UAV or destroys it can harm everyone in the UAV's flight area or damage other vehicles [5]. One of the main security concerns of UAVs is GPS spoofing attacks [6]. The civil GPS specification is publicly available [7], which makes the signal highly predictable and increases the potentialrisk of tampering. Therefore, GPS spoofing has become an important research topic since an attacker could hijack a UAV, use it to eavesdrop, or attack people or objects remotely. Currently, many different methods of detecting GPS spoofing attacks are known [8; 9; 10; 11; 12]. Some of these methods allow the UAV's GPS receiver to detect spoofing attacks [8]. These techniques include the ability of the GPS receiver to analyze the received signal strength and to compare it to the normal signal strength over time. UAVs can monitor GPS satellite identification codes or continually check the time intervals to ensure their constancy. These methods can be efficient in detecting attackers with weak capabilities. However, such methods may be ineffective against complex attacks, in which an attacker can falsify the coordinates of the victim with great accuracy [9]. [PERSON] et al. proposed a method for detecting GPS spoofing attacks based on the use of two GPS receivers to check their cross-correlation [10]. This method has been tested for multiple attack scenarios and the authors have proven that it successfully detects attacks, although the method is unable to distinguish spoofing signals from genuine GPS signals and cannot detect spoofing when the signals are weak [13]. Other methods to prevent GPS spoofing, such as autonomous monitoring of receiver integrity, signal-to-noise ratio measurements, and Doppler shift detection, have been discussed [6; 14]. For instance, [PERSON] et al. proposed a method allowing the UAV to detect the source of GPS spoofing using a ground station that continuously analyzes the content and time of arrival of information about the estimated location of the UAV [2]. It has been shown that their method is efficient and detects spoofing attacks in less than 2 s and determines a counterfeit's source location after monitoring for 15 up to 150 m. [PERSON] uses the automatic GPS signal gain control in a GPS receiver to detect and alert potential spoofing attacks within the method [15]. The ability to use multiple receivers to detect GPS spoofing attacks has been presented in several previous works [16; 17; 18]. [PERSON] et al. [17] used several independent GPS receivers to detect GPS spoofing attacks. Their proposed method depends on the distance between the receivers and then measuring the distance between the specified locations of the receivers.