The next online scientific seminar of the 2nd department of the Institute of Information Technology of ANAS was held. A report on "Development of a method for detecting GPS spoofing attacks on unmanned aerial vehicles" was listened at the seminar.

Firstly, doctoral student of Institute Orkhan Valikhanli spoke about the actuality of topic, then gave general information about the safety of unmanned aerial vehicle (UAC). He noted that, UAVs and drones are one of the special applications of cyber-physical systems. UAVs have applications in logistics, agriculture, remote sensing, smart city, disaster management, military surveillance, target tracking, air and ground defense.

He noted that PUAs have a number of security vulnerabilities. He said the drones were subjected to GPS cheating (Global Positioning System), malware injection, signal disruption, Denial-of-service, and Man-in-the-Middle attack. Among these attacks, GPS deception allows an attacker to crash or hijack a UAV. Fraud attacks are attacks that falsify a GPS signal in order to manipulate the navigation system of the system with false coordinates generated by the attacker.

The speaker also informed about the existing methods in the field of detection of GPS fraud attacks. Talking about the shortcomings of the existing methods, the speaker presented a new model based on the Convolutional Neural Network (CNN), which he proposed to detect these attacks. The rapporteur said that the proposed method was tested on logs obtained during the flight of drones. He also said that the main advantage of the new approach is that there is no need for additional equipment and the accuracy is higher than its analogues. The database used during the research, the structure of the model and the results obtained were brought to the attention of the workshop participants.

There was an exchange of views on the report. The head of the department, PhD in technical sciences, Associate Professor Yadigar Imamverdiyev recommended to further deepen research, study international experience and prepare articles for the development of methods for detecting GPS spoofing attacks on unmanned aerial vehicles.