Inconsistency measure associated discretization methods to network-based intrusion detection

Rong Zhao, Yanpeng Qu, Ansheng Deng, Reyer Zwiggelaar

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)


Network intrusion is one of the most serious threats to network infrastructure and digital assets. Intrusion-detection systems detects un-authorized network access which violates the permissions settings of computer systems, networks, and information systems. Data mining is the one of the businesslike techniques amongst which are available for intrusion detection. Many data mining methods, including decision trees and rough set theory, would work better on discrete or binarized data. In data sets, on account of the existence in very large numbers, data discretization is deemed to be the data pretreatment method and such technology is very important. In this paper, the discretization methods of DFSFDP, DBSCAN, CAIM and K-means are implemented and applied to the KDD intrusion detection data set. Then four evaluation indexes are used to evaluate the effect of discretization. Moreover, with regard to the four discretization methods, their performance and accuracy are put forward and contrasted. The results of experiment acquired through using these methods on NSL-KDD dataset prove that used DFSFDP which is selected by the index of inconsistency measure performs well in terms of classification accuracy.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Proceedings
PublisherIEEE Press
ISBN (Electronic)9781509060207
Publication statusPublished - 12 Oct 2018
Event2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018 - Rio de Janeiro, Brazil
Duration: 08 Jul 201813 Jul 2018

Publication series

NameIEEE International Conference on Fuzzy Systems
ISSN (Print)1098-7584


Conference2018 IEEE International Conference on Fuzzy Systems, FUZZ 2018
CityRio de Janeiro
Period08 Jul 201813 Jul 2018


  • Discretization Method
  • Intrusion Detection
  • KDD Dataset

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