Publication: Dataset title: Industrial Control System (ICS) Network Traffic Dataset for Anomaly Detection
Authors
Fernández Maimó, Lorenzo ; Peráles Gómez, Ángel Luis ; Huertas Celdrán, Alberto ; García Clemente, Félix Jesús ; Cadenas Sarmiento, Cristina ; Canto Masa, Carlos Javier del ; Méndez Nistal, Rubén
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info:eu-repo/semantics/dataset
Description
This dataset contains network traffic data captured from a real Industrial Control
System (ICS) testbed, designed to support research on cybersecurity, intrusion
detection, and anomaly detection in industrial environments.
The dataset has been generated from a laboratory-scale industrial installation
that emulates a real operational scenario, including Programmable Logic Controllers
(PLCs), industrial communication protocols, and controlled cyber-attack scenarios.
Traffic includes both normal operation and malicious behavior introduced through
Man-in-the-Middle (MitM) attacks.
The dataset is intended for academic and research purposes, particularly for the
evaluation of Machine Learning and Deep Learning techniques applied to ICS
cybersecurity.
Abstract
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Citation
Ángel Luis Peráles Gómez, Lorenzo Fernández Maimó, Alberto Huertas Celdrán, Félix J. García Clemente, Cristina Cadenas Sarmiento, Carlos Javier del Canto Masa, Rubén Méndez Nistal, “On the Generation of Anomaly Detection Datasets in Industrial Control Systems”, IEEE Access, 7, 177460-177473, 2019. (JCR-2019 (35/156[Q1] – Computer Science, Inf Systems) – 3,745) https://doi.org/10.1109/ACCESS.2019.2958284
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