Record Details

DATA MINING BASED TECHNIQUE FOR IDS ALERT CLASSIFICATION

International Journal of Electronic Commerce Studies

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Field Value
 
Title DATA MINING BASED TECHNIQUE FOR IDS ALERT CLASSIFICATION
 
Creator Gabra, Hany Nashat; Ain Shams University
Bahaa-Eldin, Ayman M.; Ain Shams University
Mohammed, Hoda Korashy; Ain Shams University
 
Subject Intrusion Detection; Data Mining; Frequent Pattern; Frequent Itemset
 
Description Intrusion detection systems (IDSs) have become a widely used measure for security systems. The main problem for such systems is the irrelevant alerts. We propose a data mining based method for classification to distinguish serious and irrelevant alerts with a performance of 99.9%, which is better in comparison with the other recent data mining methods that achieved 97%. A ranked alerts list is also created according to the alert’s importance to minimize human interventions.To cite this document: Hany Nashat Gabra, Ayman M. Bahaa-Eldin, and Hoda Korashy Mohammed, "Data mining based technique for ids alert classification", International Journal of Electronic Commerce Studies, Vol.6, No.1, pp.119-126, 2015.Permanent link to this document:http://dx.doi.org/10.7903/ijecs.1392
 
Publisher Academy of Taiwan Information Systems Research
 
Contributor Center for Education and Research of Information Assurance and Security (CERIAS), Purdue University, USA.
 
Date 2015-06-30
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
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Format application/pdf
 
Identifier http://academic-pub.org/ojs/index.php/ijecs/article/view/1392
 
Source International Journal of Electronic Commerce Studies; Vol 6, No 1 (2015); 119-126
2073-9729
 
Language eng
 
Relation http://academic-pub.org/ojs/index.php/ijecs/article/view/1392/285
 
Rights Copyright (c) 2015 International Journal of Electronic Commerce Studies