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Comparative Study of Different Models before Feature Selection and AFTER Feature Selection for Intrusion Detection

by Janmejay Pant, Bhaskar Pant, Amit Juyal
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 98 - Number 14
Year of Publication: 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 },
issue_date = { July 2014 },
volume = { 98 },
number = { 14 },
month = { July },
year = { 2014 },
issn = { 0975-8887 },
pages = { 16-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume98/number14/17251-7591/ },
doi = { 10.5120/17251-7591 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:26:12.322981+05:30
%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
%J International Journal of Computer Applications
%@ 0975-8887
%V 98
%N 14
%P 16-18
%D 2014
%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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Index Terms

Computer Science
Information Sciences

Keywords

Feature selection intrusion detection NSL-KDD Weka

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