Research Article
Comparative Study of Different Models before Feature Selection and AFTER Feature Selection for Intrusion Detection
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 98 - Issue 14 |
| Published: July 2014 |
| Authors: Janmejay Pant, Bhaskar Pant, Amit Juyal |
10.5120/17251-7591
|
Janmejay Pant, Bhaskar Pant, Amit Juyal . Comparative Study of Different Models before Feature Selection and AFTER Feature Selection for Intrusion Detection. International Journal of Computer Applications. 98, 14 (July 2014), 16-18. DOI=10.5120/17251-7591
@article{ 10.5120/17251-7591,
author = { Janmejay Pant,Bhaskar Pant,Amit Juyal },
title = { Comparative Study of Different Models before Feature Selection and AFTER Feature Selection for Intrusion Detection },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 98 },
number = { 14 },
pages = { 16-18 },
doi = { 10.5120/17251-7591 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Janmejay Pant
%A Bhaskar Pant
%A Amit Juyal
%T Comparative Study of Different Models before Feature Selection and AFTER Feature Selection for Intrusion Detection%T
%J International Journal of Computer Applications
%V 98
%N 14
%P 16-18
%R 10.5120/17251-7591
%I Foundation of Computer Science (FCS), NY, USA
Abstract
A network data set may contain a huge amount of data and processing this huge amount of data is one of the most challenges task for network based intrusion detection system (IDS). Normally these data contain lots of redundant and irrelevant features. Feature selection approaches are used to extract the relevant features from the original data to improve the efficiency or accuracy of IDS. In this paper an effective feature selection approaches are used for the NSL KDD data set. The performance of the used classifiers measure and compared with each other.
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