Code for FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic
doi:10.4121/e08823b5-ceff-4ebc-a967-290ef9cacc7e.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future.
For a link that will always point to the latest version, please use
doi: 10.4121/e08823b5-ceff-4ebc-a967-290ef9cacc7e
doi: 10.4121/e08823b5-ceff-4ebc-a967-290ef9cacc7e
Datacite citation style:
van Ede, Thijs; Bortolameotti, Riccardo; Continella, Andrea; Ren, Jingjing; Dubois, Daniel J. et. al. (2023): Code for FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/e08823b5-ceff-4ebc-a967-290ef9cacc7e.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software
categories
licence
MIT
This repository contains the code for FlowPrint by the authors of the NDSS FlowPrint paper [PDF]. Please cite FlowPrint when using it in academic publications. This repository provides a stable artefact version of FlowPrint. For the most up-to-date version that receives updates, please see the Github repository.
history
- 2023-10-26 first online, published, posted
publisher
4TU.ResearchData
associated peer-reviewed publication
FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic
organizations
University of Twente (Semantics Cybersecurity & Services)
DATA
To access the source code, use the following command:
git clone https://data.4tu.nl/v3/datasets/53eca195-a7dc-4c53-9477-5afaa7b1a957.git