The Application of Fuzzy Clustering Number Algorithm in Network Intrusion Detection

Lang Guo

doi:10.4028/www.scientific.net/AMR.760-762.2220

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 760-762The Application of Fuzzy Clustering Number...

The Application of Fuzzy Clustering Number Algorithm in Network Intrusion Detection

Abstract:

In view of the defects of K-means algorithm in intrusion detection: the need of preassign cluster number and sensitive initial center and easy to fall into local optimum, this paper puts forward a fuzzy clustering algorithm. The fuzzy rules are utilized to express the invasion features, and standardized matrix is adopted to further process so as to reflect the approximation degree or correlation degree between the invasion indicator data and establish a similarity matrix. The simulation results of KDD CUP1999 data set show that the algorithm has better intrusion detection effect and can effectively detect the network intrusion data.

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Periodical:

Advanced Materials Research (Volumes 760-762)

Pages:

2220-2223

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.760-762.2220

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Online since:

September 2013

Authors:

Lang Guo

Keywords:

Fuzzy Clustering Number, Intrusion Detection, K-Means Algorithm

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