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Research Article

Year : 2015 | Volume: 3 | Issue: 2 | Pages: 74-78

Data mining for network intrusion detection system in real time

M.Vanitha1*, R. Malathi, T. Lavanya and M. Muthuraman2

DOI: 0

Corresponding author

M.Vanitha*

Department of Information Technology., J.J. College of Arts & Science, Pudukkottai

  • 1. Department of Information Technology., J.J. College of Arts & Science, Pudukkottai
  • 2. Department of Information Technology., J.J. College of Arts & Science, Pudukkottai

Received on: 11/05/2016

Revised on: 11/05/2016

Accepted on: 11/05/2016

Published on: 11/05/2016

  • M.Vanitha, R. Malathi, T. Lavanya and M. Muthuraman (2015), Data mining for network intrusion detection system in real time. Scientific Transactions in Environment and Technovation, 3(2): 74-78. doi: 10

Abstract

Intrusion detection technology is an effective approach to dealing with the problems of network security. In this paper, we present a data mining-based network intrusion detection framework in real time (NIDS). This framework is a distributed architecture consisting of sensor, data preprocessor, extractors of features and detectors. To improve efficiency, our approach adopts a novel FP-tree structure and FP-growth mining method to extract features based on FP-tree without candidate generation.

Keywords

data mining, FP-growth, intrusion detection, network, real time