RF Fingerprinting Unmanned Aerial Vehicles

<p>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.</p>

Name thesis:degree_name

Master of Science in Cybersecurity Engineering

Level thesis:degree_level

Thesis - Open Access

Discipline thesis:degree_discipline

Electrical Engineering and Computer Science

Year

2021

Author dc:creator

• Ondus, Norah

• RF fingerprint
• Machine Learning
• UAV
• Alexnet
• Computer Engineering
• Electrical and Computer Engineering
• Navigation, Guidance, Control and Dynamics

Repository record dc:identifier

https://commons.erau.edu/edt/631

OAI identifier oai:identifier

oai:commons.erau.edu:edt-1653