Classification Based on the Distribution of Average Matching Degree and Its Application to Network Intrusion Detection

Abstract

With the increasing usage of Internet for business or personal affairs, the topic of internet security is becoming an extraordinary important issue. Therefore, many techniques for intrusion detection have been studied in order to build a secure internet atmosphere. In this paper, a new classification model, which is called Distance-based Classification Model, is proposed under the framework of GNP-based Class Association Rule Mining. The model uses the concept of calculating the distance between a data and rules in each class to classify the data. The simulation of evaluating this model is carried out based on KDD99Cup database.