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Optimized intrusion detection mechanism using soft computing techniques

Ahmad, iftikhar and Azween, Abdullah and Alghamdi, Abdullah and Hussain, Muhammad (2011) Optimized intrusion detection mechanism using soft computing techniques. Telecommunication Systems, 47 . pp. 1-9. ISSN 11235-011-9541-1

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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.

Item Type:Article
Subjects:Q Science > QA Mathematics > QA76 Computer software
Departments / MOR / COE:Mission Oriented Research > Megacities
ID Code:6315
Deposited By: Assoc Prof Dr Azween Abdullah
Deposited On:02 Aug 2011 04:04
Last Modified:19 Jan 2017 08:22

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