This 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. / Dissertation (MSc)--University of Pretoria, 2013. / gm2014 / Computer Science / unrestricted
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:up/oai:repository.up.ac.za:2263/36775 |
| Date | January 2013 |
| Creators | Vural, Ickin |
| Contributors | Venter, Hein S., ickin.vural@gmail.com |
| Publisher | University of Pretoria |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| 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. |
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