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Spamming Botnet Detection using Neural Networks
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vural, Ickin Venter, Hein S. |
| Copyright Year | 2016 |
| 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. |
| Starting Page | 27 |
| Ending Page | 38 |
| Page Count | 12 |
| File Format | PDF HTM / HTML |
| DOI | 10.5220/0004089800270038 |
| Alternate Webpage(s) | http://www.scitepress.org/papers/2012/40898/40898.pdf |
| Journal | IWSEC 2016 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
