RF Fingerprinting Unmanned Aerial Vehicles is an Embry-Riddle Aeronautical University (ERAU) thesis by Norah Ondus.

As unmanned aerial vehicles (UAVs) become increasingly accessible, their application in civil, military, and commercial sectors is expanding rapidly. The use cases range from aerial surveillance to search-and-rescue and even package delivery, contributing to the surge in UAV popularity. However, this growing popularity presents security challenges, such as impersonation attacks in drone-based delivery and UAV swarms.

To address these concerns, this project proposes an authentication system based on RF fingerprinting. Specifically, it leverages device-specific hardware impairments embedded in the transmitted RF signal to differentiate the identity of each UAV. The implementation involves using AlexNet and data augmentation techniques to achieve this authentication goal.

Publication Date– Fall 2021

RF Fingerprinting Unmanned Aerial Vehicles contains the following major sections:

  • Introduction
  • Literature Review
  • Methodology
  • Evaluation and Results
  • Conclusion and Future Work

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Author- Norah Ondus

See Also-

Classification of UAVs Using RF Fingerprints

Micro-UAV Detection and Classification from RF Fingerprints Using Machine Learning Techniques

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