Study on Machine Learning Techniques for Botnet Detection

dc.contributor.authorSilva, L. [UNESP]
dc.contributor.authorUtimura, L. [UNESP]
dc.contributor.authorCosta, K. [UNESP]
dc.contributor.authorSilva, M. [UNESP]
dc.contributor.authorPrado, S. [UNESP]
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2020-12-10T17:32:09Z
dc.date.available2020-12-10T17:32:09Z
dc.date.issued2020-05-01
dc.description.abstractThis paper presents a study on the application of machine learning techniques for botnet detection, compromised computer networks controlled by an attacker in order to perform malicious activities, such as distributed denial-of-service attacks (DDoS), data theft and others. The study aims to evaluate the efficiency of commonly used classifiers in the literature for botnet traffic classification and, to this end, we compare the results obtained from each classifier using two different approaches for feature selection, the first one taking into account the most frequently used features in problems of this nature, based on previous works, and the second one taking into account features selected by the Recursive Feature Elimination algorithm, a relatively unexplored feature selection method in the botnet detection area.en
dc.description.affiliationUniv Estadual Paulista, Bauru, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista, Bauru, SP, Brazil
dc.format.extent881-888
dc.identifierhttp://dx.doi.org/10.1109/TLA.2020.9082916
dc.identifier.citationIeee Latin America Transactions. Piscataway: Ieee-inst Electrical Electronics Engineers Inc, v. 18, n. 5, p. 881-888, 2020.
dc.identifier.doi10.1109/TLA.2020.9082916
dc.identifier.issn1548-0992
dc.identifier.urihttp://hdl.handle.net/11449/195369
dc.identifier.wosWOS:000532329800009
dc.language.isoeng
dc.publisherIeee-inst Electrical Electronics Engineers Inc
dc.relation.ispartofIeee Latin America Transactions
dc.sourceWeb of Science
dc.subjectBotnet
dc.subjectMachine Learning
dc.subjectRecursive Feature Elimination
dc.titleStudy on Machine Learning Techniques for Botnet Detectionen
dc.typeArtigo
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee-inst Electrical Electronics Engineers Inc

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