Network Data Unsupervised Clustering to Anomaly Detection

Network Data Unsupervised Clustering to Anomaly Detection

In these days, organizations rely on the availability and security of their communication networks to perform daily operations. As a result, network data must be analyzed in order to provide an adequate level of security and to detect anomalies or malfunctions in the systems. Due to the increase of...

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Bibliographic Details
Main Authors: Manuel López-Vizcaíno, Carlos Dafonte, Francisco J. Nóvoa, Daniel Garabato, M. A. Álvarez
Format: Article
Language:English
Published: MDPI AG 2018-09-01
Series:Proceedings
Subjects:
Self-Organizing Maps
IDS
network security
categorical SOM
visualization
unsupervised clustering
Online Access:http://www.mdpi.com/2504-3900/2/18/1173

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http://www.mdpi.com/2504-3900/2/18/1173

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