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/db4fbbb9-fe7d-44b0-b8ec-02a8c81481d9

van Ede, Thijs (2023): Code for Appscanner: Automatic fingerprinting of smartphone apps from encrypted network traffic. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/db4fbbb9-fe7d-44b0-b8ec-02a8c81481d9.v1

Software

• Other Information and Computing Sciences
• Computer Software
• Information and Computing Sciences

Mobile Traffic, Security

MIT

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Thijs van Ede

This repository contains the code for for AppScanner that was implemented as part of the NDSS FlowPrint paper [PDF], it implements the Single Large Random Forest Classifier of AppScanner [PDF]. We ask people to cite both works when using the software for academic research papers.

• 2023-10-26 first online, published, posted

4TU.ResearchData

FlowPrint: Semi-Supervised Mobile-App Fingerprinting on Encrypted Network Traffic

• https://doi.org/10.1109/EuroSP.2016.40

University of Twente (Semantics Cybersecurity & Services)