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Determination of optimal cluster number in connection to SCADA

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dc.title Determination of optimal cluster number in connection to SCADA en
dc.contributor.author Vávra, Jan
dc.contributor.author Hromada, Martin
dc.relation.ispartof Advances in Intelligent Systems and Computing
dc.identifier.issn 2194-5357 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.isbn 978-3-319-57140-9
dc.date.issued 2017
utb.relation.volume 575
dc.citation.spage 136
dc.citation.epage 147
dc.event.title 6th Computer Science On-line Conference, CSOC 2017
dc.event.sdate 2017-04-26
dc.event.edate 2017-04-29
dc.type conferenceObject
dc.language.iso en
dc.publisher Springer Verlag
dc.identifier.doi 10.1007/978-3-319-57141-6_15
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-319-57141-6_15
dc.subject Anomaly detection en
dc.subject Clusters en
dc.subject Cyber security en
dc.subject Data acquisition en
dc.subject Supervisory control en
dc.description.abstract The recent evolution of cyber-attacks creates eminent pressure on information and communication systems. The increasing number of cyber-attacks and their sophistication have resulted in needs of the new type of cyber defense. The anomaly detection in relation to intrusion detection system (IDS) in connection with standard cyber defense technologies may be the answer to contemporary development in cyber security. Moreover, unsupervised anomaly detection based on K-means algorithm is broadly examined by a considerable number of researchers. Therefore, the algorithm is a solid selection in relation to intrusion detection system. However, one of the problems is to determine a proper number of cluster for the K-means. Nonetheless, there are methods to determine the optimal number of clusters. The aim of the article is to determine the number of clusters in relation to Supervisory Control and Data Acquisition system. © Springer International Publishing AG 2017. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1007387
utb.identifier.obdid 43876906
utb.identifier.scopus 2-s2.0-85018722157
utb.identifier.wok 000405338500015
utb.source d-scopus
dc.date.accessioned 2017-09-08T12:14:49Z
dc.date.available 2017-09-08T12:14:49Z
dc.description.sponsorship CZ.1.05/2.1.00/03.0089, ERDF, European Regional Development Fund
dc.description.sponsorship Internal Grant Agency [IGA/FAI/2017/003]; Ministry of the Interior of the Czech Republic [VI20152019049, VI20172019054]; Ministry of Education, Youth and Sports of the Czech Republic within the National Sustainability Programme [LO1303 (MSMT-7778/2014)]; European Regional Development Fund under the project CEBIA-Tech [CZ.1.05/2.1.00/03.0089]
utb.contributor.internalauthor Vávra, Jan
utb.contributor.internalauthor Hromada, Martin
utb.fulltext.affiliation Jan Vávra, Martin Hromada Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stráněmi 4511, Zlín, Czech Republic {jvavra,hromada}@fai.utb.cz
utb.fulltext.dates -
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Applied Informatics
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