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Classification of Attack for IDS Using Binary Genetic Algorithm Based Feature Selection

S. Rani1

  1. Department of Computer Science and Application, Kurukshetra University, Kurukshetra, Haryana, India.
  2. Department of Computer Science and Application, Kurukshetra University, Kurukshetra, Haryana, India.

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-5 , Page no. 203-208, May-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i5.203208

Online published on May 31, 2018

Copyright © S. Rani . 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: S. Rani, “Classification of Attack for IDS Using Binary Genetic Algorithm Based Feature Selection,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.5, pp.203-208, 2018.

MLA Style Citation: S. Rani "Classification of Attack for IDS Using Binary Genetic Algorithm Based Feature Selection." International Journal of Computer Sciences and Engineering 6.5 (2018): 203-208.

APA Style Citation: S. Rani, (2018). Classification of Attack for IDS Using Binary Genetic Algorithm Based Feature Selection. International Journal of Computer Sciences and Engineering, 6(5), 203-208.

BibTex Style Citation:
@article{Rani_2018,
author = {S. Rani},
title = {Classification of Attack for IDS Using Binary Genetic Algorithm Based Feature Selection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2018},
volume = {6},
Issue = {5},
month = {5},
year = {2018},
issn = {2347-2693},
pages = {203-208},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1963},
doi = {https://doi.org/10.26438/ijcse/v6i5.203208}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i5.203208}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1963
TI - Classification of Attack for IDS Using Binary Genetic Algorithm Based Feature Selection
T2 - International Journal of Computer Sciences and Engineering
AU - S. Rani
PY - 2018
DA - 2018/05/31
PB - IJCSE, Indore, INDIA
SP - 203-208
IS - 5
VL - 6
SN - 2347-2693
ER -

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Abstract

IDS is used to detect any kinds of attacks that may harm the safety of systems. A capable IDS system needs low FAR, and high accuracy. In this paper, we have used fully distinct DM approaches on IDS with the KDD data set. Here the BGA which offers a new method used for fixing normal & DOS.

Key-Words / Index Term

Intrusion Detection System, Binary Genetic Algorithm(BGA), Classifiers, Anomaly Detection

References

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