Anomaly based Intrusion Detection System using Genetic Algorithm and K-Centroid Clustering

Abstract

See, stats, and : https : / / www . researchgate . net / publication / 316174762 Anomaly using -Centroid Clustering Article DOI : 10 . 5120 / ijca2017913762 CITATIONS 0 READS 17 3 , including : Some : Sentiment Bangla Md Shahjalal 22 SEE All . The . All - text and , letting . ABSTRACT Internet is being expanded because of the enhancement of today ' s networks and with these expansion different types of unauthorized activities building up to make the network vulnerable . Many researchers are working around the world to protect the systems from any kind of unauthorized access . In this study we have implemented an Intrusion Detection System based on K - Centroid Clustering and Genetic Algorithm to achieve a better detection rate and false positive rate . In our system training set is classified into different clusters based on K - Centroid clustering and then GA is performed to check each connection of the test set and finally result has been obtained for every specific connection . We have used both Kdd99Cup and NSLKDD dataset to get the experiment result of our system . Finally analyzing with those data we have got a decent detection rate in our implemented system .