Title: Intrusion Detection Based on K-means Clustering Analysis
Abstract: This paper introduces an intrusion detection model based on clustering analysis and realizes an algorithm of K-means which can set up a database of intrusion detection and classify safe levels. This detection system can be set up without experiential data, which is capable of re-classifying intrusion behaviors in terms of related data automatically. The technique is applicable and self-adaptable.
Publication Year: 2009
Publication Date: 2009-01-01
Language: en
Type: article
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