Botnet Detection Approach for the Distributed Systems
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.
Recommended Citation
O. Savenko et al., "Botnet Detection Approach for the Distributed Systems," Proceedings of the 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems (2019, Metz, France), vol. 1, pp. 406 - 411, Institute of Electrical and Electronics Engineers (IEEE), Sep 2019.
The definitive version is available at https://doi.org/10.1109/IDAACS.2019.8924428
Meeting Name
10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS 2019 (2019: Sep. 18-21, Metz, France)
Department(s)
Computer Science
Keywords and Phrases
Attacks; Botnet; Botnet Detection; Distributed systems; Malware; Naive Bayes classifier; Network security
International Standard Book Number (ISBN)
978-172814069-8
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 Sep 2019
