Model for Network Intrusion Detection Based on Machine Learning

Abstract

Intrusion Detection is an important step to ensure security in computer networks. In this paper, a novel model for intrusion detection is presented. The model has been developed using various existing machine learning techniques viz. decision tree, Naive Bayes, KNN and logistic regression techniques. Preexisting database of network intrusion is used to analyze the performance of the proposed model. As seen from the experimental results, the decision tree gives the best outcome with an accuracy of 96%.