Date of Award
Thesis - Open Access
Master of Science in Cybersecurity Engineering
Electrical Engineering and Computer Science
Laxima Niure Kandel, Ph.D.
First Committee Member
Dr. Houbing Song, Ph.D.
Second Committee Member
Dr. Omar Ochoa, Ph.D.
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.
Scholarly Commons Citation
Ondus, Norah, "RF Fingerprinting Unmanned Aerial Vehicles" (2021). Doctoral Dissertations and Master's Theses. 631.