Por favor, use este identificador para citar o enlazar este ítem: https://hdl.handle.net/10259/11041
Título
Flow-Based IoT Datasets for Cyberattack Detection and Generalization Studies (NFStream and Tranalyzer Tools) [Dataset]
Autor
Editorial
Universidad de Burgos
Fecha de publicación
2025-11-04
DOI
10.71486/vcgm-fe66
Zusammenfassung
This repository provides flow-based IoT traffic datasets generated through NFStream and Tranalyzer for cyberattack detection and generalization studies.
The datasets originate from two data sources:
(1) **UBU-LAB**, representing traffic captured in controlled IoT laboratory conditions, and
(2) **ToN-IoT**, a public dataset containing benign and Denial-of-Service (DoS) traffic traces (available at https://research.unsw.edu.au/projects/toniot-datasets).
All datasets have been processed and structured to support experiments on flow extraction tool comparison and cross-domain generalization using Multilayer Perceptron (MLP) models.
The repository contains:
- Raw extracted flows for both NFStream and Tranalyzer,
- Balanced datasets used in comparative studies (Paper 2), and
- Datasets generated for generalization strategies (Paper 3).
The data files are ready to be reused or integrated into new modelling pipelines for IoT network security research.
Palabras clave
IoT
Cybersecurity
Flow-based Datasets
NFStream
Tranalyzer
ToN-IoT
UBU-LAB
Generalization
Machine learning
Materia
Redes informáticas-Medidas de seguridad
Computer networks-Security measures
Seguridad informática
Computer security
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Dateien zu dieser Ressource
Tamaño:
202.2Mb
Formato:
zip









