Integrated soft computing for intrusion detection on computer network security
Date
2011
ISBN
978-145772058-1
Journal Title
Journal ISSN
Volume Title
Resource Type
Conference paper
Publisher
Journal Title
Integrated soft computing for intrusion detection on computer network security
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Abstract
Computer network security is very important for all business sectors. The Intrusion Detection Systems (IDS) is one technique that prevents an information system from a computer networks attacker. The IDS is able to detect behavior of new attacker which is indicated both correct Detection Rate and False Alarm Rate. This paper presents the new intrusion detection technique that applied hybrid of unsupervised/supervised learning scheme. To combine between the Independent Component Analysis (ICA) and the Support Vector Machine (SVM) are the advantage of these new IDS. The benefit of the ICA is to separate these independent components from the monitored variables. And the SVM is able to classify a different groups of data such as normal or anomalous. As a result, the new IDS are able to improve the performance of anomaly intrusion detection and intrusion detection. © 2011 IEEE.
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Citation
ICCAIE 2011 - 2011 IEEE Conference on Computer Applications and Industrial Electronics