2026-08-19T08:20:20Zhttps://riubu.ubu.es/oai/requestoai:riubu.ubu.es:10259/110372025-11-07T12:30:49Zcom_10259_2604col_10259_5684
Repositorio Institucional de la Universidad de Burgos
author
Martínez González, Branly Alberto
author
Díez Bermejo, Alejandro
author
Pérez Sevilla, Malena
author
Rincón Arango, Jaime Andrés
author
Urda Muñoz, Daniel
2025-11-06T13:33:06Z
2025-11-06T13:33:06Z
2025-11-04
Martinez Gonzalez, B. A., Diez Bermejo, A., Pérez Sevilla, M., Rincon Arango, J. A., & Urda Muñoz, D. (2025). Raw Network Traffic Captures for IoT Cyberattack Detection in Fog Computing Environments [Data set]. Universidad de Burgos. https://doi.org/10.71486/DGZA-T550
https://hdl.handle.net/10259/11037
10.71486/dgza-t550
These files consist of raw network packet captures (PCAP format) obtained from controlled laboratory experiments that emulate benign and malicious Internet of Things (IoT) traffic in fog computing environments. The experiments involved resource-constrained edge devices, specifically a Raspberry Pi 4 and a Jetson Nano. Malicious traffic corresponds to Denial-of-Service (DoS) attacks executed from the Jetson Nano against the Raspberry Pi 4 within an isolated local network, while benign traffic reflects typical IoT device behavior, including alert generation, DNS requests, and telemetry or device-management communications (e.g., MQTT updates).
All captures were performed under reproducible laboratory conditions and are intended to support research on intrusion detection, IoT network behavior analysis, and the development and training of cybersecurity attack detection models.
eng
Atribución 4.0 Internacional
IoT
Cybersecurity
PCAP
Network Traffic
Fog Computing
Denial-of-Service (DoS)
Raw Network Traffic Captures for IoT Cyberattack Detection in Fog Computing Environments [Dataset]
dataset
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URL
https://riubu.ubu.es/bitstream/10259/11037/4/readme.txt
File
MD5
820bad6e8eb38326c1f9bd6900a75bd9
6531
text/plain
readme.txt
URL
https://riubu.ubu.es/bitstream/10259/11037/1/Martinez-Raw_Network%20Traffic_Captures_for_IoT-Dataset_2025.zip
File
MD5
7f131359c8daf22e9650259c208341b8
1269092760
application/zip
Martinez-Raw_Network Traffic_Captures_for_IoT-Dataset_2025.zip