DATA MINING BASED TECHNIQUE FOR IDS ALERT CLASSIFICATION
DOI:
https://doi.org/10.7903/ijecs.1392Keywords:
Intrusion Detection, Data Mining, Frequent Pattern, Frequent ItemsetAbstract
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
