Comparative Study of Machine Learning Algorithm for Intrusion Detection System

Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)

Abstract

Now a day’s, Intrusion detection is a very important research area in network security. Machine learning techniques have been applied to the field of intrusion detection. In this paper, we use KDD Cup 99’ data set for taking samples. For these samples we use classification algorithms to classify the network traffic data. In this paper, we are going to compare our results with features selected using Naive Bayes, Neural Networks. We are trying to use standard measurements like detection rate, false positive, false negative, accuracy and Confusion Matrix.

Keywords

IDS Machine learning algorithms KDDCUP99 DATASET Confusion Matrix 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringAnil Neerukonda Institute of Technology and SciencesVisakhapatnamIndia

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