Network Intrusion Detection using Machine Learning.

A novel supervised machine learning system is developed to classify network traffic whether it ismalicious or benign. To find the best model considering detection success rate, combination ofsupervised learning algorithm and feature selection method have been used. Through this study, it isfound that Artificial Neural Network (ANN) based machine learning with wrapper feature selectionoutperform support vector machine (SVM) technique while classifying network traffic. To evaluate theperformance, NSL-KDD dataset is used to classify network traffic using SVM and ANN supervisedmachine learning techniques. Comparative study shows that the proposed model is efficient than otherexisting models with respect to intrusion detection success rate.