Performance comparison between backpropagation algorithms applied to intrusion detection in computer network systems

被引：0
|
作者：
Ahmad, Iftikhar [1 ,2 ]
Ansari, M. A. [1 ,2 ]
Mohsin, Sajjad [1 ,2 ]
机构：
[1] FUUAST, Dept Comp Sci, Islamabad, Pakistan
[2] COMSATS Inst Informat Technol, Islamabad, Pakistan
来源：
RECENT ADVANCES IN SYSTEMS, COMMUNICATIONS AND COMPUTERS | 2008年
关键词：
intrusion detection; backpropagation; neural networks; IDS (Intrusion Detection System); learning algorithm; dataset;
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：
In this paper a topology of neural network intrusion detection system is proposed on which different backpropagation algorithms are benchmarked. The proposed methodology uses sampled data from KddCup99 data set, an intrusion detection attacks database that is a standard for the evaluation of intrusion detection systems. The performance of backpropagation algorithms implemented in batch mode, is addressed. A comparative analysis of algorithms is made and then the most optimum solution is selected with respect to mean square error.
引用
收藏
页码：47 / +
页数：2
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