UGC Approved Journal no 63975(19)

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Published in:

Volume 6 Issue 5
May-2019
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIRCU06017


Registration ID:
217971

Page Number

85-88

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Title

Evaluation of Correlation Feature Selection and Random Forest for Network Intrusion Detection

Abstract

Network and system security are of much importance in the present data communication world. The rapid development of the internet in the last few decades has created many security problems related to intrusions on computer and network systems. To detect intrusions using machine learning, an efficient classifier has to be established. To have better predictive accuracy, various feature selection methods are used. Correlation Feature Selection (CFS) and Random Forest techniques are discussed in this paper. Both these methods follow different approaches, the former being a filter method and the latter being an embedded method. A comparison shows that even though Random Forest has higher predictive accuracy than CFS based classifier, it is computationally expensive. Both of these techniques are suitable with their own merits and demerits.

Key Words

CFS, Random Forest, NSL KDD, Network Intrusion

Cite This Article

"Evaluation of Correlation Feature Selection and Random Forest for Network Intrusion Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.85-88, May 2019, Available :http://www.jetir.org/papers/JETIRCU06017.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"Evaluation of Correlation Feature Selection and Random Forest for Network Intrusion Detection", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp85-88, May 2019, Available at : http://www.jetir.org/papers/JETIRCU06017.pdf

Publication Details

Published Paper ID: JETIRCU06017
Registration ID: 217971
Published In: Volume 6 | Issue 5 | Year May-2019
DOI (Digital Object Identifier):
Page No: 85-88
Country: Chennai, Tamil Nadu, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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