Intelligent intrusion detection system model using rough neural network

Huai Zhi Yan*, Chang Zhen Hu, Hui Min Tan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A model of intelligent intrusion detection based on rough neural network (RNN), which combines the neural network and rough set, is presented. It works by capturing network packets to identify network intrusions or malicious attacks using RNN with sub-nets. The sub-net is constructed by detection-oriented signatures extracted using rough set theory to detect different intrusions. It is proved that RNN detection method has the merits of adaptive, high universality, high convergence speed, easy upgrading and management.

Original languageEnglish
Pages (from-to)119-122
Number of pages4
JournalWuhan University Journal of Natural Sciences
Volume10
Issue number1
DOIs
Publication statusPublished - Jan 2005

Keywords

  • Intelligent intrusion detection
  • Network security
  • Neural network
  • Rough set

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