Intrusion Detection System Based on Data Mining

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First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008)

Adelaide, Australia

January 23-January 24

ISBN: 0-7695-3090-7

	ASCII Text	x
	Zhan Jiuhua, "Intrusion Detection System Based on Data Mining," International Workshop on Knowledge Discovery and Data Mining, pp. 402-405, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008.

	BibTex	x
	@article{ 10.1109/WKDD.2008.12, author = {Zhan Jiuhua}, title = {Intrusion Detection System Based on Data Mining}, journal ={International Workshop on Knowledge Discovery and Data Mining}, volume = {0}, year = {2008}, isbn = {0-7695-3090-7}, pages = {402-405}, doi = {http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.12}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - International Workshop on Knowledge Discovery and Data Mining TI - Intrusion Detection System Based on Data Mining SN - 0-7695-3090-7 SP402 EP405 A1 - Zhan Jiuhua, PY - 2008 VL - 0 JA - International Workshop on Knowledge Discovery and Data Mining ER -

Zhan Jiuhua

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/WKDD.2008.12

Analyzed recent IDS models, the development of IDS (Intrusion Detection System), and the current and gives a brief introduction to DM (Data Mining) technology. Presented a framework of IDS based on data mining for resolving the current problems IDS is facing. The system that performs anomaly detection can detect intrusions known and unknown, reduce omissions and misstatements, improve accuracy and speed of intrusion detection and has good adaptive capacity and scalability.

Citation:

Zhan Jiuhua, "Intrusion Detection System Based on Data Mining," wkdd, pp.402-405, First International Workshop on Knowledge Discovery and Data Mining (WKDD 2008), 2008

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