Article

Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic

Authors:

Jun-feng Tian,

Yue Fu,

Ying Xu,

Jian-ling WangAuthors Info & Claims

PDCAT '05: Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies

Pages 256 - 258

https://doi.org/10.1109/PDCAT.2005.157

Published: 05 December 2005 Publication History

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Abstract

In order to improve detection performance of data mining-based intrusion detection system, this paper presents a method of combining multiple decision trees based on fuzzy logic, especially the fuzzy integral. The main idea of this method is to divide a great large dataset into several sub-datasets, mine on sub-datasets separately to construct different sub-decision trees, detect TCP data by different sub-decision trees, and then nonlinearly combine the results from multiple sub-decision trees by fuzzy integral. The experiment results show that this technique is superior to individual decision trees for intrusion detection in terms of classification accuracy.

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Alsharafat W(2018)Secure software engineering requirements in cloud environment by using anticipating learning classifier systemInternational Journal of Internet Technology and Secured Transactions10.1504/IJITST.2015.0739146:1(1-8)Online publication date: 13-Dec-2018
https://dl.acm.org/doi/10.1504/IJITST.2015.073914
Aldwairi MKhamayseh YAl-Masri M(2015)Application of artificial bee colony for intrusion detection systemsSecurity and Communication Networks10.1002/sec.5888:16(2730-2740)Online publication date: 10-Nov-2015
https://dl.acm.org/doi/10.1002/sec.588
Abadeh MMohamadi HHabibi J(2011)Design and analysis of genetic fuzzy systems for intrusion detection in computer networksExpert Systems with Applications: An International Journal10.1016/j.eswa.2010.12.00638:6(7067-7075)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1016/j.eswa.2010.12.006
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Intrusion Detection Combining Multiple Decision Trees by Fuzzy logic

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PDCAT '05: Proceedings of the Sixth International Conference on Parallel and Distributed Computing Applications and Technologies

December 2005

1086 pages

ISBN:0769524052

Publisher

IEEE Computer Society

United States

Publication History

Published: 05 December 2005

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Alsharafat W(2018)Secure software engineering requirements in cloud environment by using anticipating learning classifier systemInternational Journal of Internet Technology and Secured Transactions10.1504/IJITST.2015.0739146:1(1-8)Online publication date: 13-Dec-2018
https://dl.acm.org/doi/10.1504/IJITST.2015.073914
Aldwairi MKhamayseh YAl-Masri M(2015)Application of artificial bee colony for intrusion detection systemsSecurity and Communication Networks10.1002/sec.5888:16(2730-2740)Online publication date: 10-Nov-2015
https://dl.acm.org/doi/10.1002/sec.588
Abadeh MMohamadi HHabibi J(2011)Design and analysis of genetic fuzzy systems for intrusion detection in computer networksExpert Systems with Applications: An International Journal10.1016/j.eswa.2010.12.00638:6(7067-7075)Online publication date: 1-Jun-2011
https://dl.acm.org/doi/10.1016/j.eswa.2010.12.006
Wu SBanzhaf W(2010)ReviewApplied Soft Computing10.1016/j.asoc.2009.06.01910:1(1-35)Online publication date: 1-Jan-2010
https://dl.acm.org/doi/10.1016/j.asoc.2009.06.019

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Overview of Type-2 Fuzzy Logic Systems

The development of fuzzy decision trees in the framework of Axiomatic Fuzzy Set logic

A comparative study of type-1 fuzzy logic systems, interval type-2 fuzzy logic systems and generalized type-2 fuzzy logic systems in control problems

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