RF Fingerprinting Unmanned Aerial Vehicles
dc.contributor.advisor | Laxima Niure Kandel, Ph.D | |
dc.contributor.author | NORAH ABDULLAH ONDUS | |
dc.date | 2021 | |
dc.date.accessioned | 2022-06-04T18:42:23Z | |
dc.date.available | 2022-01-19 00:01:04 | |
dc.date.available | 2022-06-04T18:42:23Z | |
dc.description.abstract | As unmanned aerial vehicles (UAVs) continue to become more readily available, their use in civil, military, and commercial applications is growing significantly. From aerial surveillance to search-and-rescue to package delivery the use cases of UAVs are accelerating. This accelerating popularity gives rise to numerous attack possibilities for example impersonation attacks in drone-based delivery, in a UAV swarm, etc. In order to ensure drone security, in this project we propose an authentication system based on RF fingerprinting. Specifically, we extract and use the device-specific hardware impairments embedded in the transmitted RF signal to separate the identity of each UAV. To achieve this goal, AlexNet with the data augmentation technique was employed. | |
dc.format.extent | 46 | |
dc.identifier.other | 109759 | |
dc.identifier.uri | https://drepo.sdl.edu.sa/handle/20.500.14154/64304 | |
dc.language.iso | en | |
dc.publisher | Saudi Digital Library | |
dc.title | RF Fingerprinting Unmanned Aerial Vehicles | |
dc.type | Thesis | |
sdl.degree.department | Cybersecurity Engineering | |
sdl.degree.grantor | Embry Riddle Aeronautical University | |
sdl.thesis.level | Master | |
sdl.thesis.source | SACM - United States of America |