Name
Abstract | ||
|---|---|---|
This article presents the technique for botnet detection using the distributed systems in the local area network. Distributed system contains host and network levels. At the host level, the botnets detection is based on Bayes classification. In order to perform the classification, the classes and subclasses were constructed on the basis of botnets patterns. An algorithm for classifier training was developed. The network level provides the exchange of the classification results for the knowledge transfer to the rest of the antivirus program units of the distributed system. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/IDAACS.2019.8924428 | 2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) |
Keywords | Field | DocType |
malware,botnet,botnet detection,distributed systems,attacks,naive Bayes classifier,network security | Naive Bayes classifier,Computer science,Botnet,Knowledge transfer,Network security,Local area network,Artificial intelligence,Classifier (linguistics),Malware,Machine learning,Bayes' theorem,Distributed computing | Conference |
Volume | ISBN | Citations |
1 | 978-1-7281-4070-4 | 0 |
PageRank | References | Authors |
0.34 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oleg Savenko | 1 | 0 | 0.68 |
| Anatoliy Sachenko | 2 | 0 | 1.01 |
| Sergii Lysenko | 3 | 0 | 0.68 |
| George Markowsky | 4 | 658 | 353.44 |