Spamming Botnet Detection using Neural Networks

Ickin Vural, Hein Venter

Abstract

The dramatic revolution in the way that we can share information has come about both through the Internet and through the dramatic increase in the use of mobile phones, especially in developing nations. Mobile phones are now found everywhere in the developing world. In 2002, the total number of mobile phones in use worldwide exceeded the number of landlines and these mobile devices are becoming increasingly sophisticated. For many people in developing countries their primary access point to the internet is a mobile device. Malicious software (malware) currently infects large numbers of mobile devices. Once infected, these mobile devices may be used to send spam SMSs. Mobile networks are now infected by malicious software such as Botnets. 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 use of a neural network.

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Paper Citation


in Harvard Style

Vural I. and Venter H. (2012). Spamming Botnet Detection using Neural Networks . In Proceedings of the 9th International Workshop on Security in Information Systems - Volume 1: WOSIS, (ICEIS 2012) ISBN 978-989-8565-15-0, pages 27-38. DOI: 10.5220/0004089800270038


in Bibtex Style

@conference{wosis12,
author={Ickin Vural and Hein Venter},
title={Spamming Botnet Detection using Neural Networks},
booktitle={Proceedings of the 9th International Workshop on Security in Information Systems - Volume 1: WOSIS, (ICEIS 2012)},
year={2012},
pages={27-38},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004089800270038},
isbn={978-989-8565-15-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Workshop on Security in Information Systems - Volume 1: WOSIS, (ICEIS 2012)
TI - Spamming Botnet Detection using Neural Networks
SN - 978-989-8565-15-0
AU - Vural I.
AU - Venter H.
PY - 2012
SP - 27
EP - 38
DO - 10.5220/0004089800270038