A New Model of Intrusion Detection Based on Data Warehouse and Data Mining

Abstract:

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Now, security of network is threaten from double layers inside and outside network, the inherent defect of firewall technology makes the intrusion detection and network traffic analysis as the main means of defense, aiding firewall. Now network intrusion detection have problem of higher false alarm rate, we apply the data warehouse and the data mining in intrusion detection and the technology of network traffic monitoring and analysis, propose a new model of intrusion detection based on the data warehouse and the data mining. The experimental result indicates this model can find effectively many kinds behavior of network intrusion and have higher intelligence and environment accommodation.

Info:

Periodical:

Advanced Materials Research (Volumes 383-390)

Edited by:

Wu Fan

Pages:

303-307

DOI:

10.4028/www.scientific.net/AMR.383-390.303

Citation:

B. Qi and Y. F. Dong, "A New Model of Intrusion Detection Based on Data Warehouse and Data Mining", Advanced Materials Research, Vols. 383-390, pp. 303-307, 2012

Online since:

November 2011

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Price:

$38.00

[1] Pei J, Han J, Mao R. CLOSET: An EfficientAlgorithm for Mining Frequent Closed Itemsets [J]. Proc. 2000 ACM-SIGMOD Int. Workshop onData Mining and Knowledge Discovery (DMKD'00) , 2000: 132-196.

[2] Sdkant. Fast Algorithms for Mining Association Rules and Sequential Patterns[C]. Madison: University of Wisconsin, 2003. 24(5): 324~355.

[3] YQiao X.W. Xin, YBin, s. Ge. Anomaly inrtusion deteetion method basedon HMM. Eleetronies Letters, Vol. 38, No. 13,P. P663—664, 20 Jun (2002).

[4] E. Eskin. Anomaly deteetion over noisy data using leanred Probability distributions Proceedings of ICML 2000. Menlo Park, CA, (2002).

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