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A unit-circle classification algorithm to characterize back attack and normal traffic for intrusion detection

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1 Author(s)
Suthaharan, S. ; Dept. of Comput. Sci., Univ. of North Carolina at Greensboro, Greensboro, NC, USA

A simple, yet effective, unit-circle algorithm for an intrusion detection system is presented. It defines normal and abnormal classes using the normalized “standard scores” of the traffic data with a novel unit-circle representation. In this approach, the feature values of the traffic data are first standardized to reduce statistical dependencies of local structural variations within a class and then normalized to isolate statistical inaccuracies between classes. A unit-circle is then constructed using two selected features. The unit-circle algorithm reveals that the normal and the back attack traffic in NSL-KDD datasets fall inside the normal and the abnormal classes respectively. Hence we have robust definitions for the back attack and normal traffic activities in a computer network based on NSL-KDD dataset.

Published in:

Intelligence and Security Informatics (ISI), 2012 IEEE International Conference on

Date of Conference:

11-14 June 2012