Combating mobile spam through Botnet detection using artificial immune systems

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dc.contributor.author Vural, Ickin
dc.contributor.author Venter, H.S. (Hein)
dc.date.accessioned 2012-08-30T10:22:50Z
dc.date.available 2012-08-30T10:22:50Z
dc.date.issued 2012-03-28
dc.description.abstract Malicious software (malware) infects large numbers of mobile devices. Once infected these mobile devices may be involved in many kinds of online criminal activity, including identity theft, unsolicited commercial SMS messages, scams and massive coordinated attacks. Until recently, mobile networks have been relatively isolated from the Internet, so there has been little need to protect them against Botnets. Mobile networks are now well integrated with the internet, so threats on the internet, such as Botnets, have started to migrate to mobile networks. This paper studies the potential threat of Botnets based on mobile networks, and proposes the use of computational intelligence techniques to detect Botnets. We then simulate mobile Bot detection by detecting anomalies using an artificial immune system implementation on an Android device. en_US
dc.description.uri http://www.jucs.org/;internal&action=noaction&Parameter=1208164030958 en_US
dc.identifier.citation Vural, I & Venter, HS 2012, 'Combating mobile spam through Botnet detection using artificial immune systems', Journal of Universal Computer Science, vol. 18, no. 6, pp. 750-774. en_US
dc.identifier.issn 0948-695X
dc.identifier.uri http://hdl.handle.net/2263/19670
dc.language.iso en en_US
dc.publisher Graz University of Technology en_US
dc.rights © J.UCS en_US
dc.subject Botnet en_US
dc.subject Mobile en_US
dc.subject Malware en_US
dc.subject Computational intelligence en_US
dc.subject Artificial immune system en_US
dc.title Combating mobile spam through Botnet detection using artificial immune systems en_US
dc.type Article en_US


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