2026-04-19T08:01:57Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/112732026-03-16T09:20:25Zcom_10259_3847com_10259_5086com_10259_2604col_10259_8557col_10259_5684
Repositorio Institucional de la Universidad de Burgos
author
Martínez González, Branly Alberto
author
Cambra Baseca, Carlos
author
Urda Muñoz, Daniel
author
Rincón Arango, Jaime Andrés
author
Herrero Cosío, Álvaro
2026-01-23T09:00:47Z
2026-01-23T09:00:47Z
2026-01-23
Martinez Gonzalez, B. A., Cambra, C., Urda Muñoz, D., Rincon Arango, J. A., & Herrero, A. (2026). Labelled IoT Flow-Based Network Traffic Dataset for Cyberattack Detection (Version 1.0) [Data set]. Universidad de Burgos. https://doi.org/10.71486/DYXT-2R24
https://hdl.handle.net/10259/11273
10.71486/dyxt-2r24
https://ss3.scayle.es:443/riubu-1/GICAP/UBUGICAP_AI4SECIOT_v1-2026.zip
This study presents a labelled flow-based network traffic dataset collected from a controlled Internet of Things (IoT) laboratory environment. The dataset captures network communication generated by hardware-based IoT devices during normal operation, including MQTT messaging, database synchronization, and web-based monitoring, as well as during the execution of predefined cyber-attack scenarios within an isolated experimental network.
Network traffic was recorded at the packet level using passive network monitoring and stored in PCAP format. The packet captures were subsequently processed into bidirectional network flows using a flow-based traffic extraction pipeline, producing flow records with statistical and temporal attributes derived from the observed packet exchanges.
Cyberattack-related flows were identified based on predefined attack execution time intervals obtained from experimental metadata. Network flows observed outside these intervals were labelled as benign and correspond to regular device communication.
The dataset is distributed through a structured repository that includes raw packet captures, processed flow-level datasets in tabular format, and metadata files describing the experimental setup, attack scenarios, and labelling criteria. The data support flow-based analysis of IoT network traffic and the evaluation of cyberattack detection methods.
eng
Atribución 4.0 Internacional
Internet of Things
Cybersecurity
Flow features
Attack traffic
Benign traffic
Network
Ground truth
Labelling
CyberFlowIoT-GICAP: Labelled Flow-Based Network Traffic Dataset for Cyberattack Detection [Dataset]
dataset
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URL
https://riubu.ubu.es/bitstream/10259/11273/7/read_me.txt
File
MD5
72a8de9f9b9e9e3372eaef5f56b86919
8157
text/plain
read_me.txt