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Survey on Intrusion Detection System Based on Feature Classification and Selection

Madhavi Dhingra1

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 399-403, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.399403

Online published on Mar 31, 2019

Copyright © Madhavi Dhingra . 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: Madhavi Dhingra, “Survey on Intrusion Detection System Based on Feature Classification and Selection,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.399-403, 2019.

MLA Style Citation: Madhavi Dhingra "Survey on Intrusion Detection System Based on Feature Classification and Selection." International Journal of Computer Sciences and Engineering 7.3 (2019): 399-403.

APA Style Citation: Madhavi Dhingra, (2019). Survey on Intrusion Detection System Based on Feature Classification and Selection. International Journal of Computer Sciences and Engineering, 7(3), 399-403.

BibTex Style Citation:
@article{Dhingra_2019,
author = {Madhavi Dhingra},
title = {Survey on Intrusion Detection System Based on Feature Classification and Selection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {399-403},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3852},
doi = {https://doi.org/10.26438/ijcse/v7i3.399403}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.399403}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3852
TI - Survey on Intrusion Detection System Based on Feature Classification and Selection
T2 - International Journal of Computer Sciences and Engineering
AU - Madhavi Dhingra
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 399-403
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Wireless networks are facing variety of attacks nowadays. To prevent from such attacks, a few Intrusion Detection frameworks are being created to distinguish and evacuate the attacks. Intrusion detection frameworks need to manage huge information having duplicate and excess features that require moderate training and testing processes leading to higher resource utilization and poor discovery rate. The performance of the Intrusion detection frameworks depend on the accuracy of the predicted attacks. Various performance parameters are to be considered for determining accuracy of a framework. The whole process is highly dependent on the network features and thus, Feature Classification is a vital issue in intrusion detection process. This paper covers the importance of feature selection, the common feature selection methods and various feature classification approaches that have been used in the field of Intrusion Detection System. The paper has also revised about the different researches that had taken place in the relevant field.

Key-Words / Index Term

Intrusion detection System, Feature Classification, Feature selection, Wireless Attacks

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