Spamming mobile botnet detection using computational intelligence

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University of Pretoria

Abstract

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.

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Dissertation (MSc)--University of Pretoria, 2013.

Keywords

Spam, Malware, Bot, Botnet, Mobile, Computational intelligence, Artificial immune system, Bayesian spam filtering, Neural networks, UCTD

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Vural, I 2013, Spamming mobile botnet detection using computational intelligence, MSc dissertation, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/36775>