Detail publikace

Traffic Similarity Observation Using a Genetic Algorithm and Clustering

OUJEZSKÝ, V. HORVÁTH, T.

Originální název

Traffic Similarity Observation Using a Genetic Algorithm and Clustering

Typ

článek v časopise ve Web of Science, Jimp

Jazyk

angličtina

Originální abstrakt

This article presents a technique of traffic similarity observation based on the statistical method of survival analysis by using a genetic algorithm. The basis comes from the k-means clustering algorithm. The observed traffic is collected from different network sources by using a NetFlow collector. The purpose of this technique is to propose a process of finding spread malicious traffic, e.g., ransomware, and considers the possibility of implementing a genetic-based algorithm. In our solution, a chromosome is created from clustering k-means centers, and the Davies–Bouldin validity index is used as the second fitness value in the solution.

Klíčová slova

Clustering algorithms, Evolutionary computation, IP networks, Information security, Programming.

Autoři

OUJEZSKÝ, V.; HORVÁTH, T.

Vydáno

11. 11. 2018

Nakladatel

MDPI

Místo

Switzerland

ISSN

2227-7080

Periodikum

Technologies - MDPI

Ročník

6

Číslo

4

Stát

Švýcarská konfederace

Strany od

1

Strany do

10

Strany počet

10

URL

https://www.mdpi.com/2227-7080/6/4/103

Plný text v Digitální knihovně

http://hdl.handle.net/11012/137212

BibTex

@article{BUT138952,
  author="Václav {Oujezský} and Tomáš {Horváth}",
  title="Traffic Similarity Observation Using a Genetic Algorithm and Clustering
",
  journal="Technologies - MDPI",
  year="2018",
  volume="6",
  number="4",
  pages="1--10",
  doi="10.3390/technologies6040103",
  issn="2227-7080",
  url="https://www.mdpi.com/2227-7080/6/4/103"
}