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dc.contributor.authorVega Vega, Rafael Alejandro
dc.contributor.authorQuintián, Héctor
dc.contributor.authorCalvo-Rolle, José Luis
dc.contributor.authorHerrero Cosío, Álvaro 
dc.contributor.authorCorchado, Emilio 
dc.date.accessioned2023-01-17T11:47:46Z
dc.date.available2023-01-17T11:47:46Z
dc.date.issued2019-04
dc.identifier.issn1367-0751
dc.identifier.urihttp://hdl.handle.net/10259/7252
dc.description.abstractThis research proposes the analysis and subsequent characterisation of Android malware families by means of low dimensional visualisations using dimensional reduction techniques. The well-known Malgenome data set, coming from the Android Malware Genome Project, has been thoroughly analysed through the following six dimensionality reduction techniques: Principal Component Analysis, Maximum Likelihood Hebbian Learning, Cooperative Maximum Likelihood Hebbian Learning, Curvilinear Component Analysis, Isomap and Self Organizing Map. Results obtained enable a clear visual analysis of the structure of this high-dimensionality data set, letting us gain deep knowledge about the nature of such Android malware families. Interesting conclusions are obtained from the real-life data set under analysis.en
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherOxford University Presses
dc.relation.ispartofLogic Journal of the IGPL. 2019, V. 27, n. 2, p. 160-176es
dc.subjectAndroid malwareen
dc.subjectMalware familiesen
dc.subjectDimensionality reductionen
dc.subjectArtificial neural networksen
dc.subject.otherInformáticaes
dc.subject.otherComputer scienceesen
dc.titleGaining deep knowledge of Android malware families through dimensionality reduction techniquesen
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1093/jigpal/jzy030es
dc.identifier.doi10.1093/jigpal/jzy030
dc.identifier.essn1368-9894
dc.journal.titleLogic Journal of the IGPLes
dc.volume.number27es
dc.issue.number2es
dc.page.initial160es
dc.page.final176es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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