Publication:
A new mobile malware classification for SMS exploitation

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dc.Conferencecode188139
dc.Conferencedate18 August 2016 through 20 August 2016
dc.ConferencenameThe 2nd International Conference on Soft Computing and Data Mining, SCDM-2016
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorZaizi N.J.M.en_US
dc.contributor.authorSaudi M.M.en_US
dc.contributor.authorKhailani A.en_US
dc.date.accessioned2024-05-29T01:55:58Z
dc.date.available2024-05-29T01:55:58Z
dc.date.issued2017
dc.description.abstractMobile malware is ubiquitous in many malicious activities such as money stealing. Consumers are charged without their consent. This paper explores how mobile malware exploit the system calls via SMS. As a solution, we proposed a system calls classification based on surveillance exploitation system calls for SMS. The proposed system calls classification is evaluated and tested using applications from Google Play Store. This research focuses on Android operating system. The experiment was conducted using Drebin dataset which contains 5560 malware applications. Dynamic analysis was used to extract the system calls from each application in a controlled lab environment. This research has developed a new mobile malware classification for Android smartphone using a covering algorithm. The classification has been evaluated in 500 applications and 126 applications have been identified to contain malware. � Springer International Publishing AG 2017.
dc.description.natureFinalen_US
dc.description.sponsorshipIlham Perdana Telkom University, Indonesia
dc.description.sponsorshipLuthfi Ramadani Telkom University, Indonesia
dc.description.sponsorshipNur Ichsan Utama Telkom University, Indonesia
dc.description.sponsorshipUmar Yunan Telkom University, Indonesia
dc.editorGhazali R.Nawi N.M.Deris M.M.Herawan T.en_US
dc.identifier.doi10.1007/978-3-319-51281-5_46
dc.identifier.epage464
dc.identifier.isbn9783320000000
dc.identifier.issn21945357
dc.identifier.scopus2-s2.0-85009774247
dc.identifier.spage456
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85009774247&doi=10.1007%2f978-3-319-51281-5_46&partnerID=40&md5=605b8afc6af569866232e2225c0c890c
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9781
dc.identifier.volume549 AISC
dc.languageEnglish
dc.language.isoen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofAdvances in Intelligent Systems and Computing
dc.sourceScopus
dc.subjectAndroiden_US
dc.subjectBig dataen_US
dc.subjectCovering algorithmen_US
dc.subjectData classificationen_US
dc.subjectMobile malwareen_US
dc.subjectAndroid (operating system)en_US
dc.subjectBig dataen_US
dc.subjectClassification (of information)en_US
dc.subjectComputer crimeen_US
dc.subjectMalwareen_US
dc.subjectSoft computingen_US
dc.subjectAndroiden_US
dc.subjectAndroid smartphoneen_US
dc.subjectCovering algorithmsen_US
dc.subjectData classificationen_US
dc.subjectGoogle playsen_US
dc.subjectMalicious activitiesen_US
dc.subjectMobile malwareen_US
dc.subjectResearch focusen_US
dc.subjectData miningen_US
dc.titleA new mobile malware classification for SMS exploitation
dc.typeConference Paperen_US
dspace.entity.typePublication

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