Name
Abstract | ||
|---|---|---|
Malicious software (malware) infects large numbers of computers around the world. This malware can be used to promote unwanted products, disseminate offensive content, or provide unauthorized access to personal and financial information. 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 onto mobile networks. Botnets on mobile devices will probably appear very soon, there are already signs that this is happening. 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 anomaly detection followed by an interpretation of the simulated values. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/978-3-642-15877-3_7 | FIS |
Keywords | Field | DocType |
anomaly detection,mobile network,offensive content,financial information,paper study,infects large number,mobile device,network forensics,mobile botnet detection,potential threat,malicious software,computational intelligence technique,malware,mobile,computational intelligence,botnet | Mobile computing,Anomaly detection,Network forensics,Computer security,Botnet,Computer science,Mobile device,Dissemination,Malware,The Internet | Conference |
Volume | ISSN | ISBN |
6369 | 0302-9743 | 3-642-15876-5 |
Citations | PageRank | References |
14 | 0.76 | 6 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ickin Vural | 1 | 23 | 2.09 |
| Hein S. Venter | 2 | 273 | 49.79 |