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Botnet Detection Approach Based on DNS

  • Sergii Lysenko
  • , Kira Bobrovnikova
  • , Bohdan Savenko
  • , Piotr Gaj
  • , Oleg Savenko
  • Khmelnytsky National University

Wyniki badań: Wkład do czasopismaArtykuł z konferencjirecenzja

4 Cytowania z bazy Scopus

Abstrakt

Botnets that use DNS technology are a serious threat on the Internet today. The potential of botnets is very large, from the spread of malware, ransomware, spam mailings to the theft of confidential information and money from bank accounts. Analysis of known methods and means of identification of botnets that use DNS has demonstrated the insufficient level of detection capacity of this type of botnets. Therefore, it is necessary to improve the method of botnets detection. The paper presents botnet detection approach based on DNS. The paper proposes a method of identifying botnets that use DNS based on the Decision Tree classifier with the application of the AdaBoost algorithm. The method allows you to ensure the detection of botnets that use DNS based on the characteristics of this technology of malicious software. The Decision Tree application algorithm is argued by the fact that it is a powerful tool for classification and prediction, and to strengthen the work of the above classifier, the AdaBoost algorithm was used in the study.

Język oryginałuangielski
Strony (od–do)400-410
Liczba stron11
CzasopismoCEUR Workshop Proceedings
Tom3156
Status publikacjiOpublikowano - 2022
Wydarzenie3rd International Workshop on Intelligent Information Technologies and Systems of Information Security, IntelITSIS 2022 - Khmelnytskyi, Ukraina
Czas trwania: 23 mar 202225 mar 2022

Obszary tematyczne ASJC Scopus

  • Informatyka ogólna

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