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12

GECCO
2004
Springer

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Network Intrusion Detection Using Genetic Clustering

13 years 9 months ago

Network Intrusion Detection Using Genetic Clustering

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Abstract. We apply the Unsupervised Niche Clustering (UNC), a genetic niching technique for robust and unsupervised clustering, to the intrusion detection problem. Using the normal samples, UNC generates clusters sumarizing the normal space. These clusters can be characterized by fuzzy membership functions, that are later aggregated to determine a level of normality. Anomalies are identiﬁed by their low normality levels.

Elizabeth Leon, Olfa Nasraoui, Jonatan Góme

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GECCO 2004 | Intrusion Detection Problem | UNC Generates Clusters | Unsupervised Clustering |

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Added	01 Jul 2010
Updated	01 Jul 2010
Type	Conference
Year	2004
Where	GECCO
Authors	Elizabeth Leon, Olfa Nasraoui, Jonatan Gómez

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