Intrusion Detection System Using Hybrid Classification Technique
R. Wankhede1 , V. Chole2
Section:Research Paper, Product Type: Journal Paper
Volume-4 ,
Issue-11 , Page no. 30-33, Nov-2016
Online published on Nov 29, 2016
Copyright © R. Wankhede, V. Chole . 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: R. Wankhede, V. Chole, “Intrusion Detection System Using Hybrid Classification Technique,” International Journal of Computer Sciences and Engineering, Vol.4, Issue.11, pp.30-33, 2016.
MLA Style Citation: R. Wankhede, V. Chole "Intrusion Detection System Using Hybrid Classification Technique." International Journal of Computer Sciences and Engineering 4.11 (2016): 30-33.
APA Style Citation: R. Wankhede, V. Chole, (2016). Intrusion Detection System Using Hybrid Classification Technique. International Journal of Computer Sciences and Engineering, 4(11), 30-33.
BibTex Style Citation:
@article{Wankhede_2016,
author = {R. Wankhede, V. Chole},
title = {Intrusion Detection System Using Hybrid Classification Technique},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2016},
volume = {4},
Issue = {11},
month = {11},
year = {2016},
issn = {2347-2693},
pages = {30-33},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1100},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1100
TI - Intrusion Detection System Using Hybrid Classification Technique
T2 - International Journal of Computer Sciences and Engineering
AU - R. Wankhede, V. Chole
PY - 2016
DA - 2016/11/29
PB - IJCSE, Indore, INDIA
SP - 30-33
IS - 11
VL - 4
SN - 2347-2693
ER -
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Abstract
Cyber Security is one of the key elements of any system. Breaching of cyber security can lead to loss of confidential and private data. To prevent the attacks on network an Intrusion Detection System Using Hybrid Classification Technique is proposed. This IDS uses a decision tree algorithm to classify the known attack types in the dataset and SVM is used to classify the normal data from the dataset, there by detecting the unknown attacks. Dataset used is the NSL-KDD Dataset.
Key-Words / Index Term
AdTree, SVM, NSL-KDD, IDS
References
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