Publication:
Android Mobile Malware Surveillance Exploitation via Call Logs: Proof of Concept

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dc.Conferencecode123957
dc.Conferencedate25 March 2015 through 27 March 2015
dc.Conferencename17th UKSim-AMSS International Conference on Computer Modelling and Simulation, UKSim 2015
dc.citedby5
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorSaudi M.M.en_US
dc.contributor.authorRidzuan F.en_US
dc.contributor.authorBasir N.en_US
dc.contributor.authorNabila N.F.en_US
dc.contributor.authorPitchay S.A.en_US
dc.contributor.authorAhmad I.N.en_US
dc.date.accessioned2024-05-29T01:54:53Z
dc.date.available2024-05-29T01:54:53Z
dc.date.issued2016
dc.description.abstractThe invention of smartphone have made life easier as it is capable of providing important functions used in user's daily life. While different operating system (OS) platform was built for smartphone, Android has become one of the most popular choice. Nonetheless, it is also the most targeted platform for mobile malware attack causing financial loss to the victims. Therefore, in this research, the exploitation on system calls in Android OS platform caused by mobile malware that could lead to financial loss were examined. The experiment was conducted in a controlled lab environment using open source tools by implementing dynamic analysis on 1260 datasets from the Android Malware Genome Project. Based on the experiment conducted, a new system call classification to exploit call logs for mobile attacks has been developed using Covering Algorithm. This new system call classification can be used as a reference for other researcher in the same field to secure against mobile malware attacks by exploiting call logs. In the future, this new system call classification could be used as a basis to develop a new model to detect mobile attacks exploitation via call logs. � 2015 IEEE.
dc.description.natureFinalen_US
dc.editorCant R.Orsoni A.Saad I.Al-Dabass D.Ibrahim Z.en_US
dc.identifier.ArtNo7576541
dc.identifier.doi10.1109/UKSim.2015.89
dc.identifier.epage181
dc.identifier.isbn9781480000000
dc.identifier.scopus2-s2.0-84991821809
dc.identifier.spage176
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84991821809&doi=10.1109%2fUKSim.2015.89&partnerID=40&md5=89b45d99e3d3abb71d25cacf3e650b3b
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9578
dc.languageEnglish
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - UKSim-AMSS 17th International Conference on Computer Modelling and Simulation, UKSim 2015
dc.sourceScopus
dc.subjectand system call classificationen_US
dc.subjectcovering algorithmen_US
dc.subjectdata transformationen_US
dc.subjectexploitation of call logs using system callsen_US
dc.subjectsimilarity analysisen_US
dc.subjectSystem callsen_US
dc.subjectComputer crimeen_US
dc.subjectIntrusion detectionen_US
dc.subjectLossesen_US
dc.subjectMalwareen_US
dc.subjectMetadataen_US
dc.subjectSignal encodingen_US
dc.subjectSmartphonesen_US
dc.subjectAndroid malwareen_US
dc.subjectCovering algorithmsen_US
dc.subjectData transformationen_US
dc.subjectGenome projectsen_US
dc.subjectOpen source toolsen_US
dc.subjectProof of concepten_US
dc.subjectSimilarity analysisen_US
dc.titleAndroid Mobile Malware Surveillance Exploitation via Call Logs: Proof of Concept
dc.typeConference Paperen_US
dspace.entity.typePublication

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