Affiliation:
1. University of Colorado Boulder
Abstract
Excerpted from "Matthan: Drone Presence Detection by Identifying Physical Signatures in the Drone's RF Communication," from MobiSys 2017, Proceedings of the 15th Annual ACM International Conference on Mobile Systems, Applications, and Services, with permission. https://dl.acm.org/citation.cfm?id=3081354 © ACM 2017.
The rapidly increasing attention regarding drone privacy and security issues requires a robust solution in both detecting and characterizing unauthorized drones. We have designed a RF-based, cost-effective and passive drone detection system, named Matthan, based on two key physical signatures of the drones, i.e., body shifting and body vibration, in the drone's wireless communication channel. In realizing Matthan, there are many open challenges in wireless sensing and networking, software-defined radio deployment, network synchronization to passively and accurately detect, localize, and characterize drones.
Publisher
Association for Computing Machinery (ACM)
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