Security Enrichment in Intrusion Detection System Using Classifier Ensemble
Joint Authors
Mali, Suresh N.
Salunkhe, Uma R.
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-12
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
In the era of Internet and with increasing number of people as its end users, a large number of attack categories are introduced daily.
Hence, effective detection of various attacks with the help of Intrusion Detection Systems is an emerging trend in research these days.
Existing studies show effectiveness of machine learning approaches in handling Intrusion Detection Systems.
In this work, we aim to enhance detection rate of Intrusion Detection System by using machine learning technique.
We propose a novel classifier ensemble based IDS that is constructed using hybrid approach which combines data level and feature level approach.
Classifier ensembles combine the opinions of different experts and improve the intrusion detection rate.
Experimental results show the improved detection rates of our system compared to reference technique.
American Psychological Association (APA)
Salunkhe, Uma R.& Mali, Suresh N.. 2017. Security Enrichment in Intrusion Detection System Using Classifier Ensemble. Journal of Electrical and Computer Engineering،Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1175234
Modern Language Association (MLA)
Salunkhe, Uma R.& Mali, Suresh N.. Security Enrichment in Intrusion Detection System Using Classifier Ensemble. Journal of Electrical and Computer Engineering No. 2017 (2017), pp.1-6.
https://search.emarefa.net/detail/BIM-1175234
American Medical Association (AMA)
Salunkhe, Uma R.& Mali, Suresh N.. Security Enrichment in Intrusion Detection System Using Classifier Ensemble. Journal of Electrical and Computer Engineering. 2017. Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1175234
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1175234