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dc.contributor.authorSedano, Javier
dc.contributor.authorGonzález González, Silvia .
dc.contributor.authorChira, Camelia
dc.contributor.authorHerrero Cosío, Álvaro 
dc.contributor.authorCorchado, Emilio 
dc.contributor.authorVillar, José Ramón
dc.date.accessioned2023-01-18T12:03:20Z
dc.date.available2023-01-18T12:03:20Z
dc.date.issued2017-02
dc.identifier.issn1367-0751
dc.identifier.urihttp://hdl.handle.net/10259/7265
dc.description.abstractIn recent years, mobile devices such as smartphones, tablets and wearables have become the new paradigm of user–computer interaction. The increasing use and adoption of such devices is also leading to an increased number of potential security risks. The spread of mobile malware, particularly on popular and open platforms such as Android, has become a major concern. This paper focuses on the bad-intentioned Android apps by addressing the problem of selecting the key features of such software that support the characterization of such malware. The accurate detection and characterization of this software is still an open challenge, mainly due to its ever-changing nature and the open distribution channels of Android apps. Maximum relevance minimum redundancy and evolutionary algorithms guided by information correlation measures have been applied for feature selection on the well-known Android Malware Genome (Malgenome) dataset, attaining interesting results on the most informative features for the characterization of representative families of existing Android malware.es
dc.description.sponsorshipThis research has been partially supported through the project of the Spanish Ministry of Economy and Competitiveness RTC-2014-3059-4. The authors would also like to thank the BIO/BU01/15 and the Spanish Ministry of Science and Innovation PID 560300-2009-11.es
dc.format.mimetypeapplication/pdf
dc.language.isoenges
dc.publisherOxford University Presses
dc.relation.ispartofLogic Journal of the IGPL. 2017, V. 25, n. 1, p. 54-66es
dc.subjectFeature selectiones
dc.subjectEvolutionary computationes
dc.subjectMax-relevance min-redundancy criteriaes
dc.subjectInformation correlation coefficientes
dc.subjectAndroides
dc.subjectMalwarees
dc.subject.otherInformáticaes
dc.subject.otherComputer sciencees
dc.titleKey features for the characterization of Android malware familieses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.relation.publisherversionhttps://doi.org/10.1093/jigpal/jzw046es
dc.identifier.doi10.1093/jigpal/jzw046
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//RTC-2014-3059-4G09226606CASTILLA Y LEON/ES/SISTEMA MULTI-AGENTE INTELIGENTE PARA LA RECARGA DE VEHÍCULO ELÉCTRICO CUMPLIENDO ISO/IEC 15118 1 y 2 (PROYECTO MAS-I-REVE)/es
dc.relation.projectIDinfo:eu-repo/grantAgreement/MINECO//RTC-2014-3059-4A09019936CASTILLA Y LEON/ES/SISTEMA MULTI-AGENTE INTELIGENTE PARA LA RECARGA DE VEHÍCULO ELÉCTRICO CUMPLIENDO ISO/IEC 15118 1 y 2 (PROYECTO MAS-I-REVE)/es
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Castilla y León//BIO%2FBU01%2F15//Utilización de acelerómetros triaxiales para la caracterización de los patrones de movimiento en pacientes epilépticos/es
dc.relation.projectIDinfo:eu-repo/grantAgreement/MICINN/Plan Estatal de Investigación Científica y Técnica y de Innovación 2008-2011/PID-560300-2009-11/ES/La excelencia española en rapid manufacturing, desarrollo y aplicación de la tecnología de deformación incremental de segunda generación para aplicaciones estratégicas/ISF_2Ges
dc.identifier.essn1368-9894
dc.journal.titleLogic Journal of IGPLes
dc.volume.number25es
dc.issue.number1es
dc.page.initial54es
dc.page.final66es
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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