Hybrid Approach for Network Intrusion Detection ntrusion Detection ntrusion Detection ntrusion Detection System U sing K K K K- -Medoid Clustering Clustering and and Naïve Bayes Classification
D. Upadhyaya, Shubha Jain · 2013
All most all existing intrusion detection systems focus on lowle vel attacks, and only generate isolated alerts. They can’t find logical relations among alerts. In addition, IDS’ accuracy is low; a lot of alerts are false alerts. To reduce this problem we propose a hybrid approach which is the combination of K-Medoids clustering and Naive-Bayes classification. The proposed approach applies clustering on all data into the corresponding group and after that applies a classifier for classification purpose. The proposed work will explore Naive-Bayes Classification and K-Medoid methods for intrusion detection and how it is useful for IDS. Naive Bayes Classification can be mined to find the