Analysis of KDD CUP 99 Dataset using Clustering based Data Mining

Abstract

The KDD Cup 99 dataset has been the point of attraction for many researchers in the field of intrusion detection from the last decade. Many researchers have contributed their efforts to analyze the dataset by different techniques. Analysis can be used in any type of industry that produces and consumes data, of course that includes security. This paper is an analysis of 10% of KDD cup'99 training dataset based on intrusion detection. We have focused on establishing a relationship between the attack types and the protocol used by the hackers, using clustered data. Analysis of data is performed using k-means clustering; we have used the Oracle 10g data miner as a tool for the analysis of dataset and build 1000 clusters to segment the 494,020 records. The investigation revealed many interesting results about the protocols and attack types preferred by the hackers for intruding the networks.