Universitat Politècnica de Catalunya
Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
Universitat Politècnica de Catalunya. VIRTUOS - Virtualisation and Operating Systems
2022
Unmanned aerial vehicles (UAVs) are widely deployed in air navigation, where numerous applications use them for safety-of-life and positioning, navigation, and timing tasks. Consequently, GPS spoofing attacks are more and more frequent. The aim of this work is to enhance GPS systems of UAVs, by providing the ability of detecting and preventing spoofing attacks. The proposed solution is based on a multilayer perceptron neural network, which processes the flight parameters and the GPS signals to generate alarms signalling GPS spoofing attacks. The obtained accuracy lies between 83.23% for TEXBAT dataset and 99.93% for MAVLINK dataset.
This work was supported in part by the Catalan Government, through the program 2017-SGR-962 and the RIS3CAT DRAC project 001-P-001723, and by the EPFL, Switzerland.
Peer Reviewed
Postprint (author's final draft)
Conference report
English
Àrees temàtiques de la UPC::Informàtica::Seguretat informàtica; Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Radiocomunicació i exploració electromagnètica::Satèl·lits i ràdioenllaços; Computer security; Drone aircraft; Deep learning; Global Positioning System; Intrusion detection model; Unmanned aerial vehicles; Spoofing; Global navigation satellite system; Seguretat informàtica; Avions no tripulats; Aprenentatge profund; Sistema de posicionament global
Springer Nature
https://link.springer.com/chapter/10.1007/978-3-030-95467-3_38
info:eu-repo/grantAgreement/GENCAT/RIS3CAT/IU16-011643 VIRTUOS P6
Open Access
E-prints [73124]
