Design and evaluation of intelligent classifier based intrusion detection system
Badii, A., Patel, D. and Bragg, H. (2008) Design and evaluation of intelligent classifier based intrusion detection system. In: European and Mediterranean conference on information systems 2008 (EMCIS 2008), Al Bostan Rotana, Dubai, UAE.
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We have discovered a novel approach of intrusion detection system using an intelligent data classifier based on a self organizing map (SOM). We have surveyed all other unsupervised intrusion detection methods, different alternative SOM based techniques and KDD winner IDS methods. This paper provides a robust designed and implemented intelligent data classifier technique based on a single large size (30x30) self organizing map (SOM) having the capability to detect all types of attacks given in the DARPA Archive 1999 the lowest false positive rate being 0.04 % and higher detection rate being 99.73% tested using full KDD data sets and 89.54% comparable detection rate and 0.18% lowest false positive rate tested using corrected data sets.
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