Improving network security using genetic algorithm approach

Authors:
Zorana Banković;Dušan Stepanović;Slobodan Bojanić;Octavio Nieto-Taladriz
Affiliations:
ETSI Telecomunicación, Technical University of Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain;Faculty of Electrical Engineering, University of Belgrade, Bulevar Kralja Aleksandra 78, 11000 Beograd, Serbia;ETSI Telecomunicación, Technical University of Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain;ETSI Telecomunicación, Technical University of Madrid, Ciudad Universitaria s/n, 28040 Madrid, Spain
Venue:
Computers and Electrical Engineering
Year:
2007

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Abstract

With the expansion of Internet and its importance, the types and number of the attacks have also grown making intrusion detection an increasingly important technique. In this work we have realized a misuse detection system based on genetic algorithm (GA) approach. For evolving and testing new rules for intrusion detection the KDD99Cup training and testing dataset were used. To be able to process network data in real time, we have deployed principal component analysis (PCA) to extract the most important features of the data. In that way we were able to keep the high level of detection rates of attacks while speeding up the processing of the data.