Dataset of anomalies and malicious acts in a cyber-physical subsystem

This article presents a dataset produced to investigate how data and information quality estimations enable to detect aNomalies and malicious acts in cyber-physical systems. Data were acquired making use of a cyber-physical subsystem consisting of liquid containers for fuel or water, along with its...

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Bibliographic Details
Published inData in brief Vol. 14; no. C; pp. 186 - 191
Main Authors Laso, Pedro Merino, Brosset, David, Puentes, John
Format Journal Article
LanguageEnglish
Published Netherlands Elsevier Inc 01.10.2017
Elsevier
Subjects
Anomaly
Automatic Control Engineering
Computer Science
Cyber-physical system
Engineering
Engineering Sciences
Other
Sensor data
Signal and Image processing
Systems security
Systems security
Anomaly
Cyber-physical system
Sensor data
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Summary:This article presents a dataset produced to investigate how data and information quality estimations enable to detect aNomalies and malicious acts in cyber-physical systems. Data were acquired making use of a cyber-physical subsystem consisting of liquid containers for fuel or water, along with its automated control and data acquisition infrastructure. Described data consist of temporal series representing five operational scenarios – Normal, aNomalies, breakdown, sabotages, and cyber-attacks – corresponding to 15 different real situations. The dataset is publicly available in the .zip file published with the article, to investigate and compare faulty operation detection and characterization methods for cyber-physical systems.
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SourceType-Scholarly Journals-1
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PMCID: PMC5536820
ISSN:2352-3409
2352-3409
DOI:10.1016/j.dib.2017.07.038