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Selective Iteration based Particle Swarm Optimization (SIPSO) for Intrusion Detection System

by Sana Warsi, Yogesh Rai, Santosh Kushwaha
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 124 - Number 17
Year of Publication: 2015
Authors: Sana Warsi, Yogesh Rai, Santosh Kushwaha
10.5120/ijca2015905822

Sana Warsi, Yogesh Rai, Santosh Kushwaha . Selective Iteration based Particle Swarm Optimization (SIPSO) for Intrusion Detection System. International Journal of Computer Applications. 124, 17 ( August 2015), 24-30. DOI=10.5120/ijca2015905822

@article{ 10.5120/ijca2015905822,
author = { Sana Warsi, Yogesh Rai, Santosh Kushwaha },
title = { Selective Iteration based Particle Swarm Optimization (SIPSO) for Intrusion Detection System },
journal = { International Journal of Computer Applications },
issue_date = { August 2015 },
volume = { 124 },
number = { 17 },
month = { August },
year = { 2015 },
issn = { 0975-8887 },
pages = { 24-30 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume124/number17/22197-2015905822/ },
doi = { 10.5120/ijca2015905822 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:14:41.021745+05:30
%A Sana Warsi
%A Yogesh Rai
%A Santosh Kushwaha
%T Selective Iteration based Particle Swarm Optimization (SIPSO) for Intrusion Detection System
%J International Journal of Computer Applications
%@ 0975-8887
%V 124
%N 17
%P 24-30
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the current age Intrusion detection is an interest in and challenging area. As there are now a few exploration works are as of now done and the outcome change is in advancement. In this paper a hybrid approach has been proposed which is based on association rule mining and Selective Iteration based Particle Swarm Optimization (SIPSO). The NSL-KDD dataset is used. First normal and attack nodes are separated. Then normal node is checked for suspicious behavior. Then association rule mining is applied to form the associated for the next preprocessing. Then we apply SIPSO to check the threshold value obtained for the different intrusion types. If it is passed the threshold velocity assigned, then it will be categorized as the specific attack. We have considered a Denial of Service (DoS), User to Root (U2R), Remote to User (R2L) and Probing (Probe) attacks in this research work. The results show the improvement in detection as compared to the previous method.

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Index Terms

Computer Science
Information Sciences

Keywords

Association rule mining SIPSO DoS U2R R2L Probe

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