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dc.contributor.authorTam, K
dc.contributor.authorFeizollah, A
dc.contributor.authorAnuar, NB
dc.contributor.authorSalleh, R
dc.contributor.authorCavallaro, L
dc.date.accessioned2020-07-16T14:17:08Z
dc.date.available2020-07-16T14:17:08Z
dc.date.issued2017-01-13
dc.identifier.issn0360-0300
dc.identifier.issn1557-7341
dc.identifier.otherARTN 76
dc.identifier.urihttp://hdl.handle.net/10026.1/16065
dc.descriptionPublisher policy: author can archive post-print on institutional repository. Publisher's version/PDF cannot be used. Publisher copyright and source must be acknowledged. Must link to publisher version with statement that this is the definitive version and DOI. Must state that version on repository is the authors version
dc.description.abstract

<jats:p>With the integration of mobile devices into daily life, smartphones are privy to increasing amounts of sensitive information. Sophisticated mobile malware, particularly Android malware, acquire or utilize such data without user consent. It is therefore essential to devise effective techniques to analyze and detect these threats. This article presents a comprehensive survey on leading Android malware analysis and detection techniques, and their effectiveness against evolving malware. This article categorizes systems by methodology and date to evaluate progression and weaknesses. This article also discusses evaluations of industry solutions, malware statistics, and malware evasion techniques and concludes by supporting future research paths.</jats:p>

dc.format.extent1-41
dc.languageen
dc.language.isoen
dc.publisherAssociation for Computing Machinery (ACM)
dc.subjectAndroid
dc.subjectmalware
dc.subjectstatic analysis
dc.subjectdynamic analysis
dc.subjectdetection
dc.subjectclassification
dc.titleThe Evolution of Android Malware and Android Analysis Techniques
dc.typejournal-article
dc.typeJournal Article
plymouth.author-urlhttps://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000399116400017&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=11bb513d99f797142bcfeffcc58ea008
plymouth.issue4
plymouth.volume49
plymouth.publication-statusPublished
plymouth.journalACM Computing Surveys
dc.identifier.doi10.1145/3017427
plymouth.organisational-group/Plymouth
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering
plymouth.organisational-group/Plymouth/Faculty of Science and Engineering/School of Engineering, Computing and Mathematics
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA
plymouth.organisational-group/Plymouth/REF 2021 Researchers by UoA/UoA11 Computer Science and Informatics
plymouth.organisational-group/Plymouth/Users by role
plymouth.organisational-group/Plymouth/Users by role/Academics
dcterms.dateAccepted2016-11-01
dc.identifier.eissn1557-7341
dc.rights.embargoperiodNot known
rioxxterms.versionofrecord10.1145/3017427
rioxxterms.licenseref.urihttp://www.rioxx.net/licenses/all-rights-reserved
rioxxterms.licenseref.startdate2017-01-13
rioxxterms.typeJournal Article/Review


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