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Malicious Node Detection for Internet Traffic Analysis using Naive Bayes Classification - An Optimal Approach for Optimal results

Author(s):

R.Pravallika , Vizag Institute of Technology

Keywords:

Php Code Analyzer, Cross Site Scripting, SQL Injection, LDAP Injection, X-Path Injection, File Disclosure, File Inclusion, Protocol Injection

Abstract

Network traffic classification is a difficult yet important task in analyzing and avoiding the overheads occurred in the network traffic to optimize the internet flow. But there are very rare cases of research that have been carried out in the field of optimizing the internet traffic and also classification of internet traffic. Many existing approaches try to minimize the over head occurred and they are yet not optimal. In this project we propose an optimized classification approach of internet traffic. It analyzed the behavior of nodes and take decision by allowing or disallowing the connection of the incoming node. We focused on this by optimal classification approach i.e., Naïve Bayes Classification/Prediction for internet traffic to analyze the behavior of nodes and also for computing the posterior probabilities with respect to each node. Though there are many other approaches at present, this proposed approach is found to be suitable and efficient in classifying the network behavior.

Other Details

Paper ID: IJSRDV3I80017
Published in: Volume : 3, Issue : 8
Publication Date: 01/11/2015
Page(s): 186-191

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