DocumentCode
2862570
Title
Study on Multi-grade Intrusion Detection Model Based on Data Mining Technology
Author
Ablat, Halqam
Author_Institution
Sch. of Math. & Inf. Technol., Xinjiang Educ. Inst., Urumqi, China
fYear
2011
fDate
14-17 Oct. 2011
Firstpage
259
Lastpage
265
Abstract
Focusing on the deficiencies of conventional intrusion detection model, Wenke Lee, Salvatore J. Stolfo et al. propose the intrusion detection system based on data mining technology. It solves the problem that self-adaptability of the system is poor, and the conditions of misreport or omission are also further improved. However, as far as mass data are concerned, more and more resources need to be consumed in the intrusion detection system based on data mining technology, and the detection speed gets slower and slower. In the article, the multi-grade intrusion detection model based on data mining technology is proposed, and the objective to improve the detection speed is reached.
Keywords
data mining; security of data; data mining; multi grade intrusion detection model; Bayesian methods; Data mining; Data models; Databases; Detectors; Feature extraction; Intrusion detection; IDES model; Intrusion detection model; data mining technology; multi-grade intrusion detection model;
fLanguage
English
Publisher
ieee
Conference_Titel
Distributed Computing and Applications to Business, Engineering and Science (DCABES), 2011 Tenth International Symposium on
Conference_Location
Wuxi
Print_ISBN
978-1-4577-0327-0
Type
conf
DOI
10.1109/DCABES.2011.85
Filename
6118730
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