Title :
Study on Multi-grade Intrusion Detection Model Based on Data Mining Technology
Author_Institution :
Sch. of Math. & Inf. Technol., Xinjiang Educ. Inst., Urumqi, China
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;
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
DOI :
10.1109/DCABES.2011.85
