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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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5G Traffic Capture Dataset: User Equipment Classification in the 5G Core

Authors: Azalim de Oliveira, Leonardo; Franco Silva, Edelberto; Jerez Chaves, Luciano;

5G Traffic Capture Dataset: User Equipment Classification in the 5G Core

Abstract

Dataset file description File name Description training_data.zip Data from other public datasets used to train the ML models inference_data.zip Data collected and used to run the model inference step File name For training or inference? 5G traffic type Description Youtube_cellular.pcap Training eMMB Video reproduction traffic collected from the "5G Traffic Datasets" public dataset naver5g3-10M.pcap Training URLLC Video live stream traffic collected from the "5G Traffic Datasets" public dataset training_data_mmtc.zip Training mMTC UDP traffic collected from the "5G Campus Networks: Measurement Traces" public dataset youtube-1M-1080p.pcap Inference eMMB Captured while virtual UE reproduced the "5G eMBB traffic" Youtube playlist naver-tv-1M.pcap Inference URLLC Captured while virtual UE reproduced the NaverTV's YTN "Korea 24-hour news channel" live stream udp-100pps.pcap Inference mMTC Captured while virtual UE used our traffic generator/Netcat to send 100 UDP packets per second udp-nc-traffic-1k.pcap Inference mMTC Captured while virtual UE used our traffic generator/Netcat to mimic an IoT-like UDP communication pattern (with variable intervals)

The data was split in two ZIP files (training_data.zip and inference_data.zip). If using them with our source code, they should be extracted to the same folder called "pcap". For more details on the expected folder structure, see the directory structure files in this other Zenodo record

A 5G dataset containing network traffic capture files created on a simulated environment and saved in the PCAP format These datasets were used in the masters dissertation titled "User Equipment Classification in the 5G Core" according to the description in the Table of contents below

The network packets of the inference dataset were captured using tcpdump on Ubuntu Linux and saved using the PCAP file format (which is more detailed than CSV) The virtual environment used free5GC and UERANSIM to simulate the 5G network

The training data was obtained from the IEEE Dataport "5G Traffic Datasets" and "5G Campus Networks: Measurement Traces" public datasets. The files' contents were not changed.

Related Organizations
Keywords

network traffic capture, Telecommunications networks, PCAP, 5g

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average