Authors: Savio Sciancalepore, Omar Adel Ibrahim, Gabriele Oligeri, Roberto Di Pietro

Date: 11th of June, 2019

 

This page is dedicated to the distribution of the source data related to the research work:

“PiNcH: an Effective, Efficient, and Robust Solution to Drone Detection via Network Traffic Analysis”

actually submitted for publication and under review.
Interested readers can download the data by clicking HERE.
The archive that you can download contains the following folders:

– static_movement: it contains source data related to a drone hovering or moving randomly in all the directions;
– drone_identification: it contains the source files of the traces downloaded from the CRAWDAD dataset, mixed with the trace of a drone moving randomly;
– movement_discrimination: it contains the source data related to a 2-minutes acquisition of every specific movement performed by the drone;
– packet_loss: it contains the source data acquired by locating the eavesdropping equipment at increasing distances from the location of the drone.

The reported source data are provided in the .txt format, being loadable from any generic data-oriented program, such as Matlab or Octave.
For any questions, please refer to the following e-mail address: ssciancalepore@hbku.edu.qa

Enjoy with the data!