Comparative Analysis of Classification Methods and Suitable Datasets for Protocol Recognition in Operational Technologies

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dc.contributor.authorHolasová, Evacs
dc.contributor.authorFujdiak, Radekcs
dc.contributor.authorMišurec, Jiřícs
dc.coverage.issue5cs
dc.coverage.volume17cs
dc.date.accessioned2024-10-14T09:03:30Z
dc.date.available2024-10-14T09:03:30Z
dc.date.issued2024-05-11cs
dc.description.abstractThe interconnection of Operational Technology (OT) and Information Technology (IT) has created new opportunities for remote management, data storage in the cloud, real-time data transfer over long distances, or integration between different OT and IT networks. OT networks require increased attention due to the convergence of IT and OT, mainly due to the increased risk of cyber-attacks targeting these networks. This paper focuses on the analysis of different methods and data processing for protocol recognition and traffic classification in the context of OT specifics. Therefore, this paper summarizes the methods used to classify network traffic, analyzes the methods used to recognize and identify the protocol used in the industrial network, and describes machine learning methods to recognize industrial protocols. The output of this work is a comparative analysis of approaches specifically for protocol recognition and traffic classification in OT networks. In addition, publicly available datasets are compared in relation to their applicability for industrial protocol recognition. Research challenges are also identified, highlighting the lack of relevant datasets and defining directions for further research in the area of protocol recognition and classification in OT environments.en
dc.formattextcs
dc.format.extent1-20cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationAlgorithms. 2024, vol. 17, issue 5, p. 1-20.en
dc.identifier.doi10.3390/a17050208cs
dc.identifier.issn1999-4893cs
dc.identifier.orcid0000-0002-5584-2948cs
dc.identifier.orcid0000-0002-8319-0633cs
dc.identifier.orcid0000-0002-5023-7757cs
dc.identifier.other188600cs
dc.identifier.researcheridABG-5140-2020cs
dc.identifier.scopus56610269000cs
dc.identifier.urihttps://hdl.handle.net/11012/249486
dc.language.isoencs
dc.publisherMDPIcs
dc.relation.ispartofAlgorithmscs
dc.relation.urihttps://www.mdpi.com/1999-4893/17/5/208cs
dc.rightsCreative Commons Attribution 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1999-4893/cs
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/cs
dc.subjectclassification methodsen
dc.subjectdatasetsen
dc.subjectmachine learningen
dc.subjectoperational technologyen
dc.subjectprotocol classificationen
dc.subjectprotocol recognitionen
dc.subjectsecurityen
dc.titleComparative Analysis of Classification Methods and Suitable Datasets for Protocol Recognition in Operational Technologiesen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
eprints.grantNumberinfo:eu-repo/grantAgreement/TA0/FW/FW07010004cs
sync.item.dbidVAV-188600en
sync.item.dbtypeVAVen
sync.item.insts2024.10.14 11:03:30en
sync.item.modts2024.09.20 13:32:06en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
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