Detecting file types using machine learning algorithms

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dc.authorscopusid57197834621
dc.authorscopusid57215282178
dc.authorscopusid57215278651
dc.authorscopusid57197831977
dc.authorscopusid56952927700
dc.contributor.authorKonaray, Serdar Korhan
dc.contributor.authorToprak, Aykut
dc.contributor.authorPek, Gamze Mat
dc.contributor.authorAkçekoce, Hüseyin
dc.contributor.authorKılınç, Deniz
dc.date.accessioned2022-02-15T16:58:03Z
dc.date.available2022-02-15T16:58:03Z
dc.date.issued2019
dc.departmentBakırçay Üniversitesien_US
dc.descriptionInnovations in Intelligent Systems and Applications Conference (ASYU) -- OCT 31-NOV 02, 2019 -- Izmir, TURKEYen_US
dc.description.abstractIn this study, experiments have been carried out to analyze the file content and classify the type of file using machine learning algorithms. First a new benchmark dataset was created including popular file types used as malicious software. Then the proposed system was trained using different machine learning algorithms. The accuracy and runtime performance comparison of models were evaluated. As a result, the highest accuracy rate was obtained as 97.83% by XGBoost algorithm.en_US
dc.description.sponsorshipYasar Univ, IEEE Turkey Sect, Yildiz Teknik Univ, Idea, Siemensen_US
dc.description.sponsorshipDeytek Bilisim [7180104]en_US
dc.description.sponsorshipThe application of the proposed study was supported and implemented by Deytek Bilisim within the scope of TUBITAK TEYDEB 1507 project (project number is 7180104 and the project name is Bilgi Geri Getirim Tabanli Kurumsal Akilli Dosya Indeksleme, Tarama Ve Filtreleme Sistemi)en_US
dc.identifier.endpage136en_US
dc.identifier.isbn978-1-7281-2868-9
dc.identifier.scopus2-s2.0-85078329939en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage133en_US
dc.identifier.urihttps://hdl.handle.net/20.500.14034/334
dc.identifier.urihttps://doi.org/10.1109/ASYU48272.2019.8946393
dc.identifier.wosWOS:000631252400025en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.journal2019 Innovations In Intelligent Systems And Applications Conference (Asyu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectContent based file type detectionen_US
dc.subjectfile type detection with machine learningen_US
dc.titleDetecting file types using machine learning algorithmsen_US
dc.typeConference Objecten_US

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