RT dataset
T1 CyberFlowIoT-GICAP: Labelled Flow-Based Network Traffic Dataset for Cyberattack Detection [Dataset]
A1 Martínez González, Branly Alberto
A1 Cambra Baseca, Carlos
A1 Urda Muñoz, Daniel
A1 Rincón Arango, Jaime Andrés
A1 Herrero Cosío, Álvaro
K1 Internet of Things
K1 Cybersecurity
K1 Flow features
K1 Attack traffic
K1 Benign traffic
K1 Network
K1 Ground truth
K1 Labelling
K1 Redes informáticas
K1 Computer networks
K1 Seguridad informática
K1 Computer security
AB 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.
PB Universidad de Burgos
YR 2026
FD 2026-01-23
LK https://hdl.handle.net/10259/11273
UL https://hdl.handle.net/10259/11273
LA eng
NO 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
NO This publication is part of the AI4SECIoT project (“Artificial Intelligence for Securing IoT Devices”), funded by the National Cybersecurity Institute (INCIBE), derived from a collaboration agreement signed between the National Institute of Cybersecurity (INCIBE) and the University of Burgos. This initiative was carried out within the framework of the Recovery, Transformation, and Resilience Plan funds, financed by the European Union (Next Generation).
DS Repositorio Institucional de la Universidad de Burgos
RD 28-abr-2026