Diao, Y. and ZHANG, Y. (2022) Drone Authentication via Acoustic Fingerprint. [Data Collection]

Collection description

This artifact consists of raw drone audio recordings and experiment code. Drone audio recordings include all the audio mentioned in Table 1. Additionally, the size of all raw drone audio recordings is about 2.9 gigabytes in the WAV format. Based on that, the experiment code can generate the four MFCC-based datasets: DS1, DS2, DS1N, and DS2N, which are mentioned in the paper. Furthermore, this code can reproduce all the experiment results in Sections 4 and 5 of our paper.

College / School:	College of Science and Engineering > School of Engineering
Date Deposited:	18 Oct 2022 13:19
URI:	https://researchdata.gla.ac.uk/id/eprint/1348
Additional details Additional details Type of data: Video Collection period: From To 27 February 2022 5 May 2022 Date: 14 September 2022 Resource language: English Data Publisher: University of Glasgow Copyright holders: University of Glasgow Last Modified: 18 Oct 2022 13:20

Available Files

Data

ACSAC_2022_Dron ... thentication.7z ACSAC_2022_Dron ... thentication.7z ACSAC_2022_Dron ... thentication.7z Visible to: Anyone Content type: Data Metadata Revision: 3 Mime-Type: application/x-7z-compressed License: Creative Commons: Attribution 4.0 File size: 1GB

Read me

readme.txt readme.txt readme.txt Visible to: Anyone Content type: Read me Metadata Revision: 2 Mime-Type: text/plain License: Creative Commons: Attribution 4.0 File size: 522B

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