UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 6 Issue 3
March-2019
eISSN: 2349-5162

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

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Published Paper ID:
JETIRAQ06034


Registration ID:
202060

Page Number

166-170

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Title

AN EFFICIENT NETWORK INTRUSION DETECTION BY ENSEMBLE LEARNING

Abstract

In the globe the corners of all communication trade are connected together by using advance network technology. At the same decade intruders are more effectively make attacks on the networks. Most of the intrusion detection system are developed by using single as well as hybrid algorithms but the key point is selecting the appropriate features on the dataset because the proper feature selection yields a high accuracy and reduce the false positive rate. In this paper an ensemble learning approach are introduced. The NSL-KDD dataset are habitually used in this field of intrusion detection system. The NSL-KDD dataset are preprocessed with attribute selection algorithms and the random forest algorithm by selecting the preferred features.

Key Words

IDS, Feature Selection, classification, WEKA, Machine Learning

Cite This Article

"AN EFFICIENT NETWORK INTRUSION DETECTION BY ENSEMBLE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 3, page no.166-170, March-2019, Available :http://www.jetir.org/papers/JETIRAQ06034.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

"AN EFFICIENT NETWORK INTRUSION DETECTION BY ENSEMBLE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 3, page no. pp166-170, March-2019, Available at : http://www.jetir.org/papers/JETIRAQ06034.pdf

Publication Details

Published Paper ID: JETIRAQ06034
Registration ID: 202060
Published In: Volume 6 | Issue 3 | Year March-2019
DOI (Digital Object Identifier):
Page No: 166-170
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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