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primary topic: Optimized intrusion detection mechanism using soft computing techniques

Optimized intrusion detection mechanism using soft computing techniques
type: AcademicArticle
type: Article
abstract: Intrusion detection is an important technique in computer and network security. A variety of intrusion detection approaches be present to resolve this severe issue but the main problem is performance. It is important to increase the detection rates and reduce false alarm rates in the area of intrusion detection. Therefore, in this research, an optimized intrusion detection mechanism using soft computing techniques is proposed to overcome performance issues. The KDD-cup dataset is used that is a benchmark for evaluating the security detection mechanisms. The Principal Component Analysis (PCA) is applied to transform the input samples into a new feature space. The selecting of an appropriate number of principal components is a critical problem. So, Genetic Algorithm (GA) is used in the optimum selection of principal components instead of using traditional method. The Support Vector Machine (SVM) is used for classification purpose. The performance of this approach is addresses. Further, a comparative analysis is made with existing approaches. Consequently, this method provides optimal intrusion detection mechanism which is capable to minimize amount of features and maximize the detection rates. © 2011 Springer Science+Business Media, LLC.
date: 2013
volume: 52
issue: 4
is part of: Telecommunication Systems
status: peerReviewed
status: published
author list: authors
type: EPrint
type: ArticleEPrint
is part of: repository

Telecommunication Systems
type: Collection
issn: 10184864

I. Ahmad
type: Person
given name: I.
family name: Ahmad

A. Abdullah
type: Person
given name: A.
family name: Abdullah

A. Alghamdi
type: Person
given name: A.
family name: Alghamdi

M. Hussain
type: Person
given name: M.
family name: Hussain

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primary topic: Optimized intrusion detection mechanism using soft computing techniques