Decision Tree with Sensitive Pruning in Network-based Intrusion Detection System

Yee Jian Chew, Shih Yin Ooi, Kok Seng Wong, Ying Han Pang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Machine learning techniques have been extensively adopted in the domain of Network-based Intrusion Detection System (NIDS) especially in the task of network traffics classification. A decision tree model with its kinship terminology is very suitable in this application. The merit of its straightforward and simple “if-else” rules makes the interpretation of network traffics easier. Despite its powerful classification and interpretation capacities, the visibility of its tree rules is introducing a new privacy risk to NIDS where it reveals the network posture of the owner. In this paper, we propose a sensitive pruning-based decision tree to tackle the privacy issues in this domain. The proposed pruning algorithm is modified based on C4.8 decision tree (better known as J48 in Weka package). The proposed model is tested with the 6 percent GureKDDCup NIDS dataset.

Original languageEnglish
Title of host publicationComputational Science and Technology - 6th ICCST 2019
EditorsRayner Alfred, Yuto Lim, Haviluddin Haviluddin, Chin Kim On
PublisherSpringer Verlag
Pages1-10
Number of pages10
ISBN (Print)9789811500572
DOIs
Publication statusPublished - Jan 1 2020
Event6th International Conference on Computational Science and Technology, ICCST 2019 - Kota Kinabalu, Malaysia
Duration: Aug 29 2019Aug 30 2019

Publication series

NameLecture Notes in Electrical Engineering
Volume603
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference6th International Conference on Computational Science and Technology, ICCST 2019
CountryMalaysia
CityKota Kinabalu
Period8/29/198/30/19

Keywords

  • Decision Tree
  • GureKDDCup
  • Network-based Intrusion Detection System (NIDS)
  • Privacy
  • Sensitive Pruning
  • Weka J48

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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