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ALTERDROID: eifferential fault analysis of obfuscated smartphone malware

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: COSEC (Computer SECurity Lab)es
dc.contributor.authorSuárez de Tangil Rotaeche, Guillermo Nicolás
dc.contributor.authorEstévez Tapiador, Juan Manuel
dc.contributor.authorLombardi, Flavio
dc.contributor.authorDi Prieto, Roberto
dc.contributor.funderComunidad de Madrides
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2022-10-27T11:01:29Z
dc.date.available2022-10-27T11:01:29Z
dc.date.issued2016-04-01
dc.description.abstractMalware for smartphones has rocketed over the last years. Market operators face the challenge of keeping their stores free from malicious apps, a task that has become increasingly complex as malware developers are progressively using advanced techniques to defeat malware detection tools. One such technique commonly observed in recent malware samples consists of hiding and obfuscating modules containing malicious functionality in places that static analysis tools overlook (e.g., within data objects). In this paper, we describe ALTERDROID, a dynamic analysis approach for detecting such hidden or obfuscated malware components distributed as parts of an app package. The key idea in ALTERDROID consists of analyzing the behavioral differences between the original app and a number of automatically generated versions of it, where a number of modifications (faults) have been carefully injected. Observable differences in terms of activities that appear or vanish in the modified app are recorded, and the resulting differential signature is analyzed through a pattern-matching process driven by rules that relate different types of hidden functionalities with patterns found in the signature. A thorough justification and a description of the proposed model are provided. The extensive experimental results obtained by testing ALTERDROID over relevant apps and malware samples support the quality and viability of our proposal.en
dc.description.sponsorshipThis work was partially supported by the MINECO grant TIN2013-46469-R (SPINY: Security and Privacy in the Internet of You) and the CAM Grant S2013/ICE-3095 (CIBERDINE: Cybersecurity, Big Data, and Risks).en
dc.identifier.bibliographicCitationG. Suarez-Tangil, J. E. Tapiador, F. Lombardi and R. D. Pietro, "Alterdroid: Differential Fault Analysis of Obfuscated Smartphone Malware," in IEEE Transactions on Mobile Computing, vol. 15, no. 4, pp. 789-802, 1 April 2016, doi: 10.1109/TMC.2015.2444847.en
dc.identifier.doihttps://doi.org/10.1109/TMC.2015.2444847
dc.identifier.issn1536-1233
dc.identifier.publicationfirstpage789
dc.identifier.publicationissue4
dc.identifier.publicationlastpage802
dc.identifier.publicationtitleIEEE TRANSACTIONS ON MOBILE COMPUTINGen
dc.identifier.publicationvolume15
dc.identifier.urihttps://hdl.handle.net/10016/35941
dc.identifier.uxxiAR/0000017902
dc.language.isoeng
dc.publisherIEEEen
dc.relation.projectIDGobierno de España. TIN-2013-46469-Res
dc.relation.projectIDComunidad de Madrid. S2013/ICE-3095es
dc.rights© 2016, IEEE
dc.rights.accessRightsopen accessen
dc.subject.ecienciaInformáticaes
dc.subject.othercomputer securityen
dc.subject.othermalwareen
dc.subject.othermobile computingen
dc.subject.otherevolutionen
dc.titleALTERDROID: eifferential fault analysis of obfuscated smartphone malwareen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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