Publication:
A New Android Botnet Classification for GPS Exploitation Based on Permission and API Calls

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dc.Conferencecode204619
dc.Conferencedate7 December 2017 through 9 December 2017
dc.Conferencename4th International Conference on Advanced Engineering Theory and Applications, AETA 2017
dc.FundingDetailsUniversiti Sains Islam Malaysia: USIM/FRGS/FST/32/50114 Ministry of Higher Education, Malaysia,�MOHE
dc.FundingDetailsAcknowledgment. The authors would like to express their gratitude to Ministry of Higher Education (MOHE), Malaysia and Universiti Sains Islam Malaysia (USIM) for the support and facilities provided. This research paper is funded by MOHE, Malaysia under grant: [USIM/FRGS/FST/32/50114].
dc.contributor.affiliationsFaculty of Science and Technology
dc.contributor.affiliationsUniversiti Sains Islam Malaysia (USIM)
dc.contributor.authorYusof M.en_US
dc.contributor.authorSaudi M.M.en_US
dc.contributor.authorRidzuan F.en_US
dc.date.accessioned2024-05-29T01:55:04Z
dc.date.available2024-05-29T01:55:04Z
dc.date.issued2018
dc.description.abstractThe target of botnet attacks has shifted from the personal computers to smartphones and mobile devices due to computational power and functionality of the mobile devices. Mobile botnet is a network consists of compromised mobile devices controlled by a botmaster through a command and control (C&C) network. Nowadays mobile botnets attacks are increasingly being used for advanced political or financial interest. Due to its popularity amongst the mobile operating system, Android has become the most targeted platform by the mobile botnets. The popularity of Android attracts the attackers to develop malicious applications with the botnet capability to hijack users� devices. In this paper, a new Android botnet classification based on GPS exploitation based on permissions and API calls is proposed using feature selection. The training was carried out using malware dataset from the Drebin and tested using 800 mobile apps from the Google Play store. The experiment was conducted using static analysis and open source tools in a controlled lab environment. This new classification can be used as a reference for other researchers in the same field to secure against GPS exploitation from Android botnet attacks. � Springer International Publishing AG 2018.
dc.description.natureFinalen_US
dc.editorKim S.B.Dao T.T.Zelinka I.Duy V.H.Phuong T.T.en_US
dc.identifier.doi10.1007/978-3-319-69814-4_3
dc.identifier.epage37
dc.identifier.isbn9783320000000
dc.identifier.issn18761100
dc.identifier.scopus2-s2.0-85034605681
dc.identifier.spage27
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85034605681&doi=10.1007%2f978-3-319-69814-4_3&partnerID=40&md5=f8d19710779841082a4e51ed776a37dc
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/9622
dc.identifier.volume465
dc.languageEnglish
dc.language.isoen_US
dc.publisherSpringer Verlagen_US
dc.relation.ispartofLecture Notes in Electrical Engineering
dc.sourceScopus
dc.subjectAndroid smartphoneen_US
dc.subjectMachine learningen_US
dc.subjectMobile botneten_US
dc.subjectMobile botnet classificationen_US
dc.subjectStatic analysisen_US
dc.subjectBotneten_US
dc.subjectComputation theoryen_US
dc.subjectLearning systemsen_US
dc.subjectMalwareen_US
dc.subjectPersonal computersen_US
dc.subjectSmartphonesen_US
dc.subjectStatic analysisen_US
dc.subjectAndroid smartphoneen_US
dc.subjectCommand and controlen_US
dc.subjectComputational poweren_US
dc.subjectGoogle playsen_US
dc.subjectMobile appsen_US
dc.subjectMobile botnetsen_US
dc.subjectMobile operating systemsen_US
dc.subjectOpen source toolsen_US
dc.titleA New Android Botnet Classification for GPS Exploitation Based on Permission and API Calls
dc.typeConference Paperen_US
dspace.entity.typePublication

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