Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm

Vulnerability detection in Supervisory Control and Data Acquisition (SCADA) network of a Smart Factory (SF) is a high-priority research area in the cyber-security domain. Choosing an efficient Machine Learning (ML) algorithm for intrusion detection is a huge challenge. This study performed an invest...

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Autores principales:	Love Allen Chijioke Ahakonye, Cosmas Ifeanyi Nwakanma, Jae-Min Lee, Dong-Seong Kim
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	Algorithms artificial intelligence machine learning SCADA systems Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/9433664b56c74b61aa209f94aac0e3ea
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spelling	oai:doaj.org-article:9433664b56c74b61aa209f94aac0e3ea2021-11-25T00:01:07ZEfficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm2169-353610.1109/ACCESS.2021.3127560https://doaj.org/article/9433664b56c74b61aa209f94aac0e3ea2021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9612219/https://doaj.org/toc/2169-3536Vulnerability detection in Supervisory Control and Data Acquisition (SCADA) network of a Smart Factory (SF) is a high-priority research area in the cyber-security domain. Choosing an efficient Machine Learning (ML) algorithm for intrusion detection is a huge challenge. This study performed an investigative analysis into the classification ability of various ML models leveraging public cyber-security datasets to determine the best model. Based on the performance evaluation, all adaptions of Decision Tree (DT) and KNN in terms of accuracy, training time, MCE, and prediction speed are the most suitable ML for resolving security issues in the SCADA system.Love Allen Chijioke AhakonyeCosmas Ifeanyi NwakanmaJae-Min LeeDong-Seong KimIEEEarticleAlgorithmsartificial intelligencemachine learningSCADA systemsElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 154892-154901 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Algorithms artificial intelligence machine learning SCADA systems Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	Algorithms artificial intelligence machine learning SCADA systems Electrical engineering. Electronics. Nuclear engineering TK1-9971 Love Allen Chijioke Ahakonye Cosmas Ifeanyi Nwakanma Jae-Min Lee Dong-Seong Kim Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm
description	Vulnerability detection in Supervisory Control and Data Acquisition (SCADA) network of a Smart Factory (SF) is a high-priority research area in the cyber-security domain. Choosing an efficient Machine Learning (ML) algorithm for intrusion detection is a huge challenge. This study performed an investigative analysis into the classification ability of various ML models leveraging public cyber-security datasets to determine the best model. Based on the performance evaluation, all adaptions of Decision Tree (DT) and KNN in terms of accuracy, training time, MCE, and prediction speed are the most suitable ML for resolving security issues in the SCADA system.
format	article
author	Love Allen Chijioke Ahakonye Cosmas Ifeanyi Nwakanma Jae-Min Lee Dong-Seong Kim
author_facet	Love Allen Chijioke Ahakonye Cosmas Ifeanyi Nwakanma Jae-Min Lee Dong-Seong Kim
author_sort	Love Allen Chijioke Ahakonye
title	Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm
title_short	Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm
title_full	Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm
title_fullStr	Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm
title_full_unstemmed	Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm
title_sort	efficient classification of enciphered scada network traffic in smart factory using decision tree algorithm
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/9433664b56c74b61aa209f94aac0e3ea
work_keys_str_mv	AT loveallenchijiokeahakonye efficientclassificationofencipheredscadanetworktrafficinsmartfactoryusingdecisiontreealgorithm AT cosmasifeanyinwakanma efficientclassificationofencipheredscadanetworktrafficinsmartfactoryusingdecisiontreealgorithm AT jaeminlee efficientclassificationofencipheredscadanetworktrafficinsmartfactoryusingdecisiontreealgorithm AT dongseongkim efficientclassificationofencipheredscadanetworktrafficinsmartfactoryusingdecisiontreealgorithm
_version_	1718414707878002688

Efficient Classification of Enciphered SCADA Network Traffic in Smart Factory Using Decision Tree Algorithm

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