What Static Analysis Can Utmost Offer for Android Malware Detection

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dc.contributor.authorKabakuş, Abdullah Talha
dc.date.accessioned2020-04-30T23:46:57Z
dc.date.available2020-04-30T23:46:57Z
dc.date.issued2019
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.descriptionWOS: 000510402300005en_US
dc.description.abstractMalicious applications are widespread for Android despite the taken serious actions by the operating system. Static and dynamic analysis techniques are utilized to detect malware by identifying the signatures of malicious applications by inspecting both the resources and behaviors of malware, respectively. In this study, what static analysis can utmost offer to detect malware in Android ecosystem is discussed and experimented on commonly used datasets in the literature by proposing a novel Android malware detection approach based on static analysis techniques. With the proposed study, the effectiveness of novel static analysis features' in terms of detecting malware in Android ecosystem are proved. These features were underestimated by the related work in the literature. The experimental result shows that the proposed Android malware detection approach is very effective in terms of detecting Android malware. Each feature used by the proposed approach is evaluated by using different types of machine learning techniques in order to highlight its impact on detecting malware and inform the digital investigators. The accuracy of the proposed static analysis approach is calculated as high as 0.987 for 10,865 applications.en_US
dc.identifier.doi10.5755/j01.itc.48.2.21457en_US
dc.identifier.endpage249en_US
dc.identifier.issn1392-124X
dc.identifier.issue2en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage235en_US
dc.identifier.urihttps://doi.org/10.5755/j01.itc.48.2.21457
dc.identifier.urihttps://hdl.handle.net/20.500.12684/5394
dc.identifier.volume48en_US
dc.identifier.wosWOS:000510402300005en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherKaunas Univ Technologyen_US
dc.relation.ispartofInformation Technology And Controlen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectAndroid malwareen_US
dc.subjectAndroid malware detectionen_US
dc.subjectstatic analysisen_US
dc.subjectmachine learningen_US
dc.subjectAndroiden_US
dc.titleWhat Static Analysis Can Utmost Offer for Android Malware Detectionen_US
dc.typeArticleen_US

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