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

Publication date: October 2017
Source:Data in Brief, Volume 14
Author(s): Pedro Merino Laso, David Brosset, John Puentes
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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