Litcius/Paper detail

BOTNET DETECTION APPROACH BASED ON THE DISTRIBUTED SYSTEMS

Олег Савенко, Anatoliy Sachenko, Sergii Lysenko, George Markowsky, Nadiia Vasylkiv

2020International Journal of Computing24 citationsDOIOpen Access PDF

Abstract

The paper presents a botnet detection approach for the distributed systems. It is based on the developed three level model, which includes botnet’s components: command and control center, control centers, basic elements of the botnet (bots). The novel framework provides the ability to detect known and unknown botnets, and consists of the host and the network levels. At the host level, the detection procedure is based on the implementation of the Bayes classification. The network level extends the results obtained at the host level to the rest of the local area network. Proposed approach provides the exchange of the results obtained by the Bayes classification for further use by other program units of the distributed system. The results of the developed classifier show that representation of the botnets’ samples for different classes and subclasses is sufficient for efficient botnet detection. Proposed technique demonstrates promising results concerning botnet detection in the distributed systems.

Topics & Concepts

BotnetComputer scienceHost (biology)Classifier (UML)Command and controlBayes' theoremNaive Bayes classifierData miningArtificial intelligenceThe InternetOperating systemSupport vector machineBayesian probabilityEcologyBiologyTelecommunicationsNetwork Security and Intrusion DetectionAdvanced Data Processing TechniquesCybersecurity and Information Systems
BOTNET DETECTION APPROACH BASED ON THE DISTRIBUTED SYSTEMS | Litcius