Spamming mobile botnet detection using computational intelligence

dc.contributor.advisorVenter, Hein S.
dc.contributor.emailickin.vural@gmail.comen_US
dc.contributor.postgraduateVural, Ickin
dc.date.accessioned2014-02-26T11:16:55Z
dc.date.available2014-02-26T11:16:55Z
dc.date.created2013-09-04
dc.date.issued2013en_US
dc.descriptionDissertation (MSc)--University of Pretoria, 2013.en_US
dc.description.abstractThis dissertation explores a new challenge to digital systems posed by the adaptation of mobile devices and proposes a countermeasure to secure systems against threats to this new digital ecosystem. The study provides the reader with background on the topics of spam, Botnets and machine learning before tackling the issue of mobile spam. The study presents the reader with a three tier model that uses machine learning techniques to combat spamming mobile Botnets. The three tier model is then developed into a prototype and demonstrated to the reader using test scenarios. Finally, this dissertation critically discusses the advantages of having using the three tier model to combat spamming Botnets.en_US
dc.description.availabilityunrestricteden_US
dc.description.departmentComputer Scienceen_US
dc.description.librariangm2014en_US
dc.identifier.citationVural, I 2013, Spamming mobile botnet detection using computational intelligence, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/36775>en_US
dc.identifier.otherE13/9/1142/gmen_US
dc.identifier.urihttp://hdl.handle.net/2263/36775
dc.language.isoenen_US
dc.publisherUniversity of Pretoriaen_ZA
dc.rights© 2013 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.en_US
dc.subjectSpamen_US
dc.subjectMalwareen_US
dc.subjectBoten_US
dc.subjectBotneten_US
dc.subjectMobileen_US
dc.subjectComputational intelligenceen_US
dc.subjectArtificial immune systemen_US
dc.subjectBayesian spam filteringen_US
dc.subjectNeural networksen_US
dc.subjectUCTDen_US
dc.titleSpamming mobile botnet detection using computational intelligenceen_US
dc.typeDissertationen_US

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