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Intrusion detection using cost-sensitive classification

Aikaterini Mitrokotsa (Institutionen för data- och informationsteknik, Nätverk och system (Chalmers) ) ; Christos Dimitrakakis (Institutionen för data- och informationsteknik, Datavetenskap, Algoritmer (Chalmers)) ; C. Douligeris
Proceedings of the 3rd European Conference on Computer Network Defense, EC2ND 2007 (2009)
[Konferensbidrag, refereegranskat]

Intrusion Detection is an invaluable part of computer networks defense. An important consideration is the fact that raising false alarms carries a significantly lower cost than not detecting attacks. For this reason, we examine how cost-sensitive classification methods can be used in Intrusion Detection systems. The performance of the approach is evaluated under different experimental conditions, cost matrices and different classification models, in terms of expected cost, as well as detection and false alarm rates. We find that even under unfavourable conditions, cost-sensitive classification can improve performance significantly, if only slightly. © Springer Science+Business Media, LLC 2009.



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Denna post skapades 2013-12-18. Senast ändrad 2015-01-08.
CPL Pubid: 189774

 

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