Bayesian based intrusion detection system

被引：47

作者：

Altwaijry, Hesham ^{[1
]}

Algarny, Saeed ^{[1
]}

机构：

[1] King Saud Univ, Comp Engn Dept, POB 51178, Riyadh 11543, Saudi Arabia

来源：

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES | 2012年 / 24卷 / 01期

关键词：

Intrusion detection system (IDS); Bayesian filter; KDD'99;

D O I：

10.1016/j.jksuci.2011.10.001

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper an intrusion detection system is developed using Bayesian probability. The system developed is a naive Bayesian classifier that is used to identify possible intrusions. The system is trained a priori using a subset of the KDD dataset. The trained classifier is then tested using a larger subset of KDD dataset. The Bayesian classifier was able to detect intrusion with a superior detection rate. (C) 2011 King Saud University. Production and hosting by Elsevier B.V. All rights reserved.

引用

页码：1 / 6

页数：6

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