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IJSDR
INTERNATIONAL JOURNAL OF SCIENTIFIC DEVELOPMENT AND RESEARCH
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2455-2631 | Impact factor: 8.15 | ESTD Year: 2016
open access , Peer-reviewed, and Refereed Journals, Impact factor 8.15

Issue: March 2024

Volume 9 | Issue 3

Impact factor: 8.15

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Paper Title: Network Intrusion Detection based on Feature set Selection using Back-Propagation Neural Network
Authors Name: Supratim Paul , Dr. R. Nagaraja , Shivakumar B R
Unique Id: IJSDR1811019
Published In: Volume 3 Issue 11, November-2018
Abstract: With dynamic increase of network application and electronic gadgets such as PCs, cell phones, and so on attacks and detection of intrusion became most challenging task in cybercrime detection zone. Decades ago, because of better network technology and more utility of the Internet, it became all digital in worldwide. Parallel to these enhancements, the endeavors of hackers for intruding the networks are also increased. And these attacks adversely affect the network badly. In this project for intrusion detection, an Artificial Neural Network (ANN) classification algorithm is implemented. The Network Layer-Knowledge Discovery Database data set is analyzed that contains of 41 features to study the viability of classification algorithm and intrusion attack detection is made by using Back-Propagation method to achieve more accuracy. Artificial neural network model gives the best number of features of 22 attributes need for detecting the intrusion and which is further categorized into more and less significant attributes. Hence, improves the accuracy and saving of resources is done.
Keywords: Intrusion Detection System, Artificial Neural Network, Feature Selection
Cite Article: "Network Intrusion Detection based on Feature set Selection using Back-Propagation Neural Network", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.3, Issue 11, page no.106 - 114, November-2018, Available :http://www.ijsdr.org/papers/IJSDR1811019.pdf
Downloads: 000336256
Publication Details: Published Paper ID: IJSDR1811019
Registration ID:180654
Published In: Volume 3 Issue 11, November-2018
DOI (Digital Object Identifier):
Page No: 106 - 114
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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