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False Positives Reduction Techniques in Intrusion Detection Systems-A Review


Asieh Mokarian, Ahmad Faraahi, Arash Ghorbannia Delavar


Vol. 13  No. 10  pp. 128-134


During the last decade with the growth of cyber attacks, information safety has become an important issue all over the world. Intrusion detection systems (IDSs) are an essential element for network security infrastructure and play a very important role in detecting large number of attacks. Although there are different types of intrusion detection systems, all these systems suffer a common problem which is generating high volume of alerts and huge number of false positives. This drawback has become the main motivation for many research papers in IDS area. The aim of conducted research in the field is to propose different techniques to handle the alerts, reduce them and distinguish real attacks from false positives and low importance events. This manuscript is a survey paper that represents a review of the current research related to the false positives problem. The focus will be on data mining techniques of alert reduction. This paper reviews more than 30 related studies during the last decade with the hope of providing a reference for further research in this area. Several open issues have also been addressed in this paper.


network security; intrusion detection system; data mining; false positive rate; alert reduction