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A Novel Cluster-based Intrusion Detection Approach Integrating Multiple Learning Techniques

by Hossein Shapoorifard, Pirooz Shamsinejad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 166 - Number 3
Year of Publication: 2017
Authors: Hossein Shapoorifard, Pirooz Shamsinejad
10.5120/ijca2017913948

Hossein Shapoorifard, Pirooz Shamsinejad . A Novel Cluster-based Intrusion Detection Approach Integrating Multiple Learning Techniques. International Journal of Computer Applications. 166, 3 ( May 2017), 13-16. DOI=10.5120/ijca2017913948

@article{ 10.5120/ijca2017913948,
author = { Hossein Shapoorifard, Pirooz Shamsinejad },
title = { A Novel Cluster-based Intrusion Detection Approach Integrating Multiple Learning Techniques },
journal = { International Journal of Computer Applications },
issue_date = { May 2017 },
volume = { 166 },
number = { 3 },
month = { May },
year = { 2017 },
issn = { 0975-8887 },
pages = { 13-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume166/number3/27649-2017913948/ },
doi = { 10.5120/ijca2017913948 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:12:42.434658+05:30
%A Hossein Shapoorifard
%A Pirooz Shamsinejad
%T A Novel Cluster-based Intrusion Detection Approach Integrating Multiple Learning Techniques
%J International Journal of Computer Applications
%@ 0975-8887
%V 166
%N 3
%P 13-16
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In order to make computer systems completely secure, in addition to firewalls and other intrusion protection devices, other systems called intrusion detection systems (IDS) are needed to detect intrusion and provide solutions to counter the intruder if he penetrated through firewall, antivirus and other security devices. Many IDS have been developed based on machine learning techniques. Specifically, advanced detection approaches created by combining or integrating multiple learning techniques have shown better detection performance than general single learning techniques. This paper proposes an improvement for a feature representation approach, namely the cluster center and nearest neighbor (CANN) approach.

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Index Terms

Computer Science
Information Sciences

Keywords

Intrusion Detection System Data Mining Hybrid Intrusion Detection System anomaly detection cluster center nearest neighbor.

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