UGC Approved Journal no 63975(19)

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

Volume 7 Issue 3
March-2020
eISSN: 2349-5162

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

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Published Paper ID:
JETIR2003085


Registration ID:
229595

Page Number

542-547

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Title

A SURVEY ON INTRUSION DETECTION SYSTEM USING MACHINE LEARNING FRAMEWORK

Abstract

Network intrusion detection systems play a crucial role in defending computer networks. In recent years, one of the main focuses within NIDS research has been the application of machine learning techniques. This paper proposes a novel deep learning model to enable NIDS operation within modern networks. The model shows a combination of deep and machine learning, capable of correctly analyzing a wide-range of network traffic. The novel approach proposes non-symmetric deep auto encoder (NDAE) for unsupervised feature learning. Moreover, additionally proposes novel deep learning classification display built utilizing stacked NDAEs. Our proposed classifier has been executed in Graphics processing unit and assessed utilizing the benchmark using KDD Cup '99 and NSL-KDD datasets. The performance evaluated network intrusion detection analysis datasets, particularly KDD Cup 99 and NSL-KDD dataset. The contribution work is to implement intrusion prevention system (IPS) contains IDS functionality but more sophisticated systems which are capable of taking immediate action in order to prevent or reduce the malicious behavior.

Key Words

Deep and machine learning, intrusion detection, Auto-encoders, KDD, Network security, Novel Approach.

Cite This Article

"A SURVEY ON INTRUSION DETECTION SYSTEM USING MACHINE LEARNING FRAMEWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 3, page no.542-547, March-2020, Available :http://www.jetir.org/papers/JETIR2003085.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

"A SURVEY ON INTRUSION DETECTION SYSTEM USING MACHINE LEARNING FRAMEWORK", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 3, page no. pp542-547, March-2020, Available at : http://www.jetir.org/papers/JETIR2003085.pdf

Publication Details

Published Paper ID: JETIR2003085
Registration ID: 229595
Published In: Volume 7 | Issue 3 | Year March-2020
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.23333
Page No: 542-547
Country: -, -, - .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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