Name
Abstract | ||
|---|---|---|
Delivery drones may become potential targets for package theft. An adversary may launch a drone impersonation attack, where the adversary's drone purports to be a legitimate delivery drone. To protect against such attacks, authenticating drones is crucial. Existing authentication schemes based on digital certificates have been shown to be compromised by security breaches on certificate authorities. Thus, we propose SoundUAV as a second factor of authentication for drones that leverages uniqueness in acoustic emanations to fingerprint drones, even within the same make and model. This uniqueness is attributed to hardware defects in motors, making SoundUAV secure against impersonation and robust to large scale attacks. Further, SoundUAV requires no hardware modifications to drones as it utilizes the pervasive acoustic emanations. We perform preliminary evaluation on eleven drones and obtain a fingerprinting accuracy of 99.48%.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3307334.3328662 | Proceedings of the 17th Annual International Conference on Mobile Systems, Applications, and Services |
Keywords | DocType | ISBN |
acoustic analysis, authentication, drones, fingerprinting | Conference | 978-1-4503-6661-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Soundarya Ramesh | 1 | 1 | 2.04 |
| Thomas Pathier | 2 | 0 | 0.34 |
| Jun Han | 3 | 7 | 2.26 |