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Integrated Technique of Junction Tree and Naive Bayes for Network Intrusion Detection System

Author(s):

Jyoti Gupta , rungta college of engineering and technology

Keywords:

IDS

Abstract

Network intrusion detection system (NIDS) monitors traffic on a network looking for doubtful activity, which could be an attack or illegal activity. The intrusion detection techniques based upon data mining are generally plummet into one of two categories: misuse detection and anomaly detection. In misuse detection, each instance in a data set is labeled as 'normal' or 'intrusive' and a learning algorithm is trained over the labeled data. In this paper we will discuss about the steps involved in NIDS, further we will compare different techniques of NIDS based on accuracy parameter i.e. precision and recall. In this paper we have proposed an integrated approach of Junction Tree and Naïve Bayes machine learning algorithm for detection of network intrusion, dataset used for experimental evaluation is KDD dataset.

Other Details

Paper ID: IJSRDV6I120088
Published in: Volume : 6, Issue : 12
Publication Date: 01/03/2019
Page(s): 108-112

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