Combating mobile spam through Botnet detection using artificial immune systems
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Date
Authors
Vural, Ickin
Venter, H.S. (Hein)
Journal Title
Journal ISSN
Volume Title
Publisher
Graz University of Technology
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.
Description
Keywords
Botnet, Mobile, Malware, Computational intelligence, Artificial immune system
Sustainable Development Goals
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.