Traffic Similarity Observation Using a Genetic Algorithm and Clustering
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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.
KeywordsClustering algorithms, Evolutionary computation, IP networks, Information security, Programming.
Document typePeer reviewed
Document versionFinal PDF
SourceTechnologies - MDPI. 2018, vol. 6, issue 4, p. 1-10.
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