A New Approach to Network Intrusion Detection Based on Gaussian Mixture Model

被引：0
|
作者：
He, Qian [1 ]
Zhang, Qian [1 ]
Wang, Lin [1 ]
Liang, Yi [1 ]
机构：
[1] Pattern Recognit & Intelligent Syst Lab Guizhou P, Guiyang 550025, Guzhou, Peoples R China
来源：
INTERNATIONAL CONFERENCE ON COMPUTATIONAL AND INFORMATION SCIENCES (ICCIS 2014) | 2014年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper presents a novel approach for detecting network intrusions. A self-adaptive modeling formula based on Gaussian features is proposed firstly. Then the model is tested by simulating network traffic data. Experimental results obtained by applying this approach to five types of intrusions, including Dos, Probe, R2L, U2R and Guess_passwd, show that the proposed approach performs exceptionally with respective accuracy of 99.91%, 98.88%, 67.36%, 69.57% and 49.08%.
引用
收藏
页码：535 / 540
页数：6
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