Design and evaluation of intelligent classifier based intrusion detection systemBadii, 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. Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. Abstract/SummaryWe 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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