SCADA System Testbed for Cybersecurity Research Using Machine Learning Approach

Marcio Andrey Teixeira, Tara Salman, Maede Zolanvari, Raj Jain, Nader Meskin and Mohammed Samaka
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Marcio Andrey Teixeira: Department of Informatics, Federal Institute of Education, Science, and Technology of Sao Paulo, Catanduva 15808-305, SP, Brazil
Tara Salman: Department of Computer Science and Engineering, Washington University in Saint Louis, Saint Louis, MO 63130, USA
Maede Zolanvari: Department of Computer Science and Engineering, Washington University in Saint Louis, Saint Louis, MO 63130, USA
Raj Jain: Department of Computer Science and Engineering, Washington University in Saint Louis, Saint Louis, MO 63130, USA
Nader Meskin: Department of Electrical Engineering, Qatar University, Doha 2713, Qatar
Mohammed Samaka: Department of Computer Science and Engineering, Qatar University, Doha 2713, Qatar

Future Internet, 2018, vol. 10, issue 8, 1-15

Abstract: This paper presents the development of a Supervisory Control and Data Acquisition (SCADA) system testbed used for cybersecurity research. The testbed consists of a water storage tank’s control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naïve Bayes and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environments.

Keywords: cybersecurity; machine learning; SCADA system; network security (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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