MagDet:UAV GPS Spoofing Detection Based on the Geomagnetic Field
GPS is currently the most widely used satellite-based navigation and positioning sys-tem.For unmanned aerial vehicles(UAVs),it is an indispensable component,providing crucial and precise location data that is essential for the success of navigation and missions.However,GPS spoofing attacks have gradually evolved into a growing threat to GPS-dependent systems.Most existing GPS spoofing detection methods for UAVs are proposed based on simulation data,and they depend on multiple UAVs or require dedicated devices(e.g.,software-defined radio platform and high-definition camera).In this paper,we propose a novel GPS spoofing detection framework,MagDet,for a UAV based on the geomagnetic field.Our basic idea is to use the geo-magnetic field anomalies due to inhomogeneities within the Earth's interior and surrounding met-al material.We collect positions and the strength of magnetic field through real flights including normal and attacked scenarios.Various machine learning algorithms are applied to train with these data to choose the best classifier,which can be easily deployed in common companion com-puter.The detection rate is more than 99.5%and the equal error rate(EER)is 0.51%,which is better than existing methods.We also evaluate various factors on MagDet to demonstrate the ro-bustness.Even in an unvisited site(6 kilometers away),the accuracy is higher than 95%and the EER is 0.49%.