Study on Intrusion Detection System Based on Data Mining

Jiang Kun Mao; Fan Zhan

doi:10.4028/www.scientific.net/AMM.713-715.2499

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 713-715Study on Intrusion Detection System Based on Data...

Study on Intrusion Detection System Based on Data Mining

Abstract:

Intrusion detection system as a proactive network security technology, is necessary and reasonable to add a static defense. However, the traditional exceptions and errors detecting exist issues of leakage police, the false alarm rate or maintenance difficult. In this paper, The intrusion detection system based on data mining with statistics, machine learning techniques in the detection performance, robustness, self-adaptability has a great advantage. The system improves the K-means clustering algorithm, focus on solving two questions of the cluster center node selection and discriminating of clustering properties, the test shows that the system further enhance the detection efficiency of the system.

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Periodical:

Applied Mechanics and Materials (Volumes 713-715)

Pages:

2499-2502

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.713-715.2499

Citation:

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Online since:

January 2015

Authors:

Jiang Kun Mao*, Fan Zhan

Keywords:

Abnormal, Clustering Shipboard, Data Mining, Intrusion Detection, Misuse

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* - Corresponding Author

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