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Machine Learning in Intrusion Detection – A Survey

P. Anitha1 , D. Rajesh2 , K. Venkata Ratnam3

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 112-119, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.112119

Online published on Mar 31, 2019

Copyright © P. Anitha, D. Rajesh, K. Venkata Ratnam . 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: P. Anitha, D. Rajesh, K. Venkata Ratnam, “Machine Learning in Intrusion Detection – A Survey,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.112-119, 2019.

MLA Style Citation: P. Anitha, D. Rajesh, K. Venkata Ratnam "Machine Learning in Intrusion Detection – A Survey." International Journal of Computer Sciences and Engineering 7.3 (2019): 112-119.

APA Style Citation: P. Anitha, D. Rajesh, K. Venkata Ratnam, (2019). Machine Learning in Intrusion Detection – A Survey. International Journal of Computer Sciences and Engineering, 7(3), 112-119.

BibTex Style Citation:
@article{Anitha_2019,
author = {P. Anitha, D. Rajesh, K. Venkata Ratnam},
title = {Machine Learning in Intrusion Detection – A Survey},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {112-119},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3806},
doi = {https://doi.org/10.26438/ijcse/v7i3.112119}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.112119}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3806
TI - Machine Learning in Intrusion Detection – A Survey
T2 - International Journal of Computer Sciences and Engineering
AU - P. Anitha, D. Rajesh, K. Venkata Ratnam
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 112-119
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

With the huge expansion of internet based services and important information on networks, network protection and security is a very significant task. Intrusion Detection system (IDS) is the standard component in network security framework and is essential to protect computer systems and network from different attacks. IDSs is designed to detect both known and unknown attacks in computer systems and networks. This paper presents different Machine Learning techniques of IDS for protecting computers and networks. This study analyzes different machine learning methods in IDS. It reviews related studies focusing on single, hybrid and ensemble classifiers with relevant datasets.

Key-Words / Index Term

Machine Learning, intrusion detection, Single Classifiers, Hybrid Classifiers, Ensemble Classifiers.

References

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