A New Intrusion Detection Method Based on Rough Sets for Network Security

Na Jiao

doi:10.4028/www.scientific.net/AMR.915-916.1311

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 915-916A New Intrusion Detection Method Based on Rough...

A New Intrusion Detection Method Based on Rough Sets for Network Security

Abstract:

In this paper, we introduce a new intrusion detection method based on rough sets for network. The first step consists of feature selection which is based on rough set theory. The next phase is clustering by using Fuzzy C-Means. Rough set theory is an efficient tool for further reducing redundancy. Fuzzy C-Means allows objects which are belong to several clusters simultaneously, with different degrees of membership. To evaluate the performance of the introduced approaches, we applied them to the international Knowledge Discovery and Data mining intrusion detection dataset. Experimental results illustrate that our algorithm is accurate models for handling complex attack patterns in large network.

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Periodical:

Advanced Materials Research (Volumes 915-916)

Pages:

1311-1314

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.915-916.1311

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Online since:

April 2014

Authors:

Na Jiao*

Keywords:

Data Mining (DM), Fuzzy C-Means, Network Intrusion Detection, Rough Set (RS)

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