A hybrid framework based on neural network MLP and means clustering for intrusion detection system

Due to the widespread use of Internet and communication networks, in case a reliable and secure network plays a crucial role for information technology (IT) service providers and users. The hardness of network attacks, as well as their complexity, has also increased lately.High false alarm rate is...

Full description

Saved in:

Bibliographic Details
Main Authors:	Lisehroodi, Mazyar Mohammadi, Muda, Zaiton, Yassin, Warusia
Format:	Conference or Workshop Item
Language:	English
Published:	2013
Subjects:	QA75 Electronic computers. Computer science
Online Access:	http://repo.uum.edu.my/12030/1/PID20.pdf http://repo.uum.edu.my/12030/ http://www.icoci.cms.net.my/proceedings/2013/TOC.html
Tags:	Add Tag No Tags, Be the first to tag this record!
Institution:	Universiti Utara Malaysia
Language:	English

id	my.uum.repo.12030
record_format	eprints
spelling	my.uum.repo.120302014-08-25T07:00:38Z http://repo.uum.edu.my/12030/ A hybrid framework based on neural network MLP and means clustering for intrusion detection system Lisehroodi, Mazyar Mohammadi Muda, Zaiton Yassin, Warusia QA75 Electronic computers. Computer science Due to the widespread use of Internet and communication networks, in case a reliable and secure network plays a crucial role for information technology (IT) service providers and users. The hardness of network attacks, as well as their complexity, has also increased lately.High false alarm rate is a big issue for majority of researches in this area.To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate.This paper provides the conceptual view and a general framework of the proposed system. 2013-08-28 Conference or Workshop Item PeerReviewed application/pdf en http://repo.uum.edu.my/12030/1/PID20.pdf Lisehroodi, Mazyar Mohammadi and Muda, Zaiton and Yassin, Warusia (2013) A hybrid framework based on neural network MLP and means clustering for intrusion detection system. In: 4th International Conference on Computing and Informatics (ICOCI 2013), 28 -30 August 2013, Kuching, Sarawak, Malaysia. http://www.icoci.cms.net.my/proceedings/2013/TOC.html
institution	Universiti Utara Malaysia
building	UUM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Utara Malaysia
content_source	UUM Institutionali Repository
url_provider	http://repo.uum.edu.my/
language	English
topic	QA75 Electronic computers. Computer science
spellingShingle	QA75 Electronic computers. Computer science Lisehroodi, Mazyar Mohammadi Muda, Zaiton Yassin, Warusia A hybrid framework based on neural network MLP and means clustering for intrusion detection system
description	Due to the widespread use of Internet and communication networks, in case a reliable and secure network plays a crucial role for information technology (IT) service providers and users. The hardness of network attacks, as well as their complexity, has also increased lately.High false alarm rate is a big issue for majority of researches in this area.To overwhelm this challenge a hybrid learning approach is proposed, employing the combination of K-means clustering and Neural Network Multi-Layer Perceptron (MLP) classification. Concerning the robustness of K-means method and MLP algorithms benefits, this research is the part of an effort to develop a hybrid information detection system (IDS) which is able to detect high percentage of novel attacks while keep the false alarm at low rate.This paper provides the conceptual view and a general framework of the proposed system.
format	Conference or Workshop Item
author	Lisehroodi, Mazyar Mohammadi Muda, Zaiton Yassin, Warusia
author_facet	Lisehroodi, Mazyar Mohammadi Muda, Zaiton Yassin, Warusia
author_sort	Lisehroodi, Mazyar Mohammadi
title	A hybrid framework based on neural network MLP and means clustering for intrusion detection system
title_short	A hybrid framework based on neural network MLP and means clustering for intrusion detection system
title_full	A hybrid framework based on neural network MLP and means clustering for intrusion detection system
title_fullStr	A hybrid framework based on neural network MLP and means clustering for intrusion detection system
title_full_unstemmed	A hybrid framework based on neural network MLP and means clustering for intrusion detection system
title_sort	hybrid framework based on neural network mlp and means clustering for intrusion detection system
publishDate	2013
url	http://repo.uum.edu.my/12030/1/PID20.pdf http://repo.uum.edu.my/12030/ http://www.icoci.cms.net.my/proceedings/2013/TOC.html
_version_	1644280800241254400

A hybrid framework based on neural network MLP and means clustering for intrusion detection system

Similar Items