OMC-IDS: at the cross-roads of OLAP mining and intrusion detection

Authors:
Hanen Brahmi;Imen Brahmi;Sadok Ben Yahia
Affiliations:
LIPAH, Computer Science Department, Faculty of Sciences of Tunis, Tunis, Tunisia;LIPAH, Computer Science Department, Faculty of Sciences of Tunis, Tunis, Tunisia;LIPAH, Computer Science Department, Faculty of Sciences of Tunis, Tunis, Tunisia,Institut TELECOM, TELECOM SudParis, UMR 5157 CNRS SAMOVAR, France
Venue:
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Year:
2012

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Abstract

Due to the growing threat of network attacks, the efficient detection as well as the network abuse assessment are of paramount importance. In this respect, the Intrusion Detection Systems (IDS) are intended to protect information systems against intrusions. However, IDS are plugged with several problems that slow down their development, such as low detection accuracy and high false alarm rate. In this paper, we introduce a new IDS, called OMC-IDS, which integrates data mining techniques and On Line Analytical Processing (OLAP) tools. The association of the two fields can be a powerful solution to deal with the defects of IDS. Our experiment results show the effectiveness of our approach in comparison with those fitting in the same trend.