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An Efficient NB-IWD Based Network Traffic Classification over KDD Dataset

Amit Kumar1 , Daya Shankar Pandey2 , Varsha Namdeo3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 706-710, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.706710

Online published on Apr 30, 2019

Copyright © Amit Kumar, Daya Shankar Pandey, Varsha Namdeo . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Amit Kumar, Daya Shankar Pandey, Varsha Namdeo, “An Efficient NB-IWD Based Network Traffic Classification over KDD Dataset,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.706-710, 2019.

MLA Style Citation: Amit Kumar, Daya Shankar Pandey, Varsha Namdeo "An Efficient NB-IWD Based Network Traffic Classification over KDD Dataset." International Journal of Computer Sciences and Engineering 7.4 (2019): 706-710.

APA Style Citation: Amit Kumar, Daya Shankar Pandey, Varsha Namdeo, (2019). An Efficient NB-IWD Based Network Traffic Classification over KDD Dataset. International Journal of Computer Sciences and Engineering, 7(4), 706-710.

BibTex Style Citation:
@article{Kumar_2019,
author = {Amit Kumar, Daya Shankar Pandey, Varsha Namdeo},
title = {An Efficient NB-IWD Based Network Traffic Classification over KDD Dataset},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {706-710},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4103},
doi = {https://doi.org/10.26438/ijcse/v7i4.706710}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.706710}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4103
TI - An Efficient NB-IWD Based Network Traffic Classification over KDD Dataset
T2 - International Journal of Computer Sciences and Engineering
AU - Amit Kumar, Daya Shankar Pandey, Varsha Namdeo
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 706-710
IS - 4
VL - 7
SN - 2347-2693
ER -

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Abstract

The Network traffic arrangement is a procedure by which the large chips get away at different parameters for instance port and convention based which are utilized to identify the classes of the traffic. Thus these types of classification methods are very helpful in providing security at two levels- network as well as system. The main focus of this paper is sorting out the problem which comes while handling network traffic whereas some of the traffic classification methods are unable to find out the special requirements of individual datasets because there are massive measures of network traffic datasets and restricted quantities of resources are accessible to deliver classification examination. The paper uncovers that traffic arrangement should be refreshed normally to keep up the precision and ought to have the capacity to adjust the dynamic conduct of network stream.

Key-Words / Index Term

Network Traffic, Network Traffic Class, Network Features, Statistical features, Classification

References

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