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Abstract: We present a new approach to anomaly detection based on the Unsupervised Niche Clustering (UNC). The UNC is a genetic niching technique for clustering that can handle noise, and is able to determine the number of clusters automatically. The UNC uses the normal samples for generating a profile of the normal space (clusters). Each cluster can later be characterized by a fuzzy membership function that follows a Gaussian shape defined by the evolved cluster centers and radii. The set of memberships ... (Update)
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BibTeX entry: (Update)
@misc{ leon-anomaly,
author = "Elizabeth Leon and Olfa Nasraoui and Jonatan Gomez",
title = "Anomaly Detection Based on Unsupervised Niche Clustering with Application
to Network Intrusion",
url = "citeseer.ist.psu.edu/718320.html" }
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http://www.phys.uni.torun.pl/kmk/projects/datasets.html
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