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Cooperative network behaviour analysis model for mobile Botnet detection

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dc.citedby7
dc.contributor.authorEslahi M.en_US
dc.contributor.authorYousefi M.en_US
dc.contributor.authorNaseri M.V.en_US
dc.contributor.authorYussof Y.M.en_US
dc.contributor.authorTahir N.M.en_US
dc.contributor.authorHashim H.en_US
dc.contributor.authorid55639528700en_US
dc.contributor.authorid53985756300en_US
dc.contributor.authorid56463729100en_US
dc.contributor.authorid35093577700en_US
dc.contributor.authorid56168849900en_US
dc.contributor.authorid16021805400en_US
dc.date.accessioned2023-05-29T06:11:30Z
dc.date.available2023-05-29T06:11:30Z
dc.date.issued2016
dc.descriptionBehavioral research; Industrial electronics; Malware; Mobile devices; Mobile security; Botnet detections; BYOD Security; Command and control; Mobile HTTP Botnet; Periodic pattern; HTTPen_US
dc.description.abstractRecently, the mobile devices are well integrated with Internet and widely used by normal users and organizations which employ Bring Your Own Device technology. On the other hand, the mobile devices are less protected in comparison to computers. Therefore, the mobile devices and networks have now become attractive targets for attackers. Amongst several types of mobile threats, the mobile HTTP Botnets can be considered as one of the most sophisticated attacks. A HTTP Bots stealthily infect mobile devices and periodically communicate with their controller called Botmaster. Although the Bots hide their activities amongst the normal web flows, their periodic pattern has been used as a measure to detect their activities. In this paper we propose a cooperative network behaviour analysis model to identify the level of periodicity posed by mobile Bots. Finally three metrics is proposed to detect Mobile HTTP Botnets based on similarity and correlation of their group activities. Test results show that the propose model can efficiently classify communication patterns into several periodicity categories and detect mobile Botnets. � 2016 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7575046
dc.identifier.doi10.1109/ISCAIE.2016.7575046
dc.identifier.epage112
dc.identifier.scopus2-s2.0-84992034514
dc.identifier.spage107
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84992034514&doi=10.1109%2fISCAIE.2016.7575046&partnerID=40&md5=f2e5a02bdef0827f24f13571e01e6409
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22656
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleISCAIE 2016 - 2016 IEEE Symposium on Computer Applications and Industrial Electronics
dc.titleCooperative network behaviour analysis model for mobile Botnet detectionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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