Traffic Similarity Observation Using a Genetic Algorithm and Clustering

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Date
2018-11-11
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Referee
Mark
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MDPI
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Abstract
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.
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Citation
Technologies - MDPI. 2018, vol. 6, issue 4, p. 1-10.
https://www.mdpi.com/2227-7080/6/4/103
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Peer-reviewed
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Published version
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en
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Defence
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Creative Commons Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
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