Gravitational search algorithm for feature selection in intrusion detection system

This project was carried out to use the Gravitational Search Algorithm for feature selection in IDS to selectively choose significant features which represents categories of network such as DoS, Probe, U2R and R2L and to improve the accuracy and effectiveness of feature selection and to have better...

Full description

Saved in:

Bibliographic Details
Main Author:	Jabali, Vahid Kaviani
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/33183/5/VahidKavianiJabaliMFSKSM2013.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.33183
record_format	uketd_dc
spelling	my-utm-ep.331832017-09-11T07:04:14Z Gravitational search algorithm for feature selection in intrusion detection system 2013-01 Jabali, Vahid Kaviani QA75 Electronic computers. Computer science This project was carried out to use the Gravitational Search Algorithm for feature selection in IDS to selectively choose significant features which represents categories of network such as DoS, Probe, U2R and R2L and to improve the accuracy and effectiveness of feature selection and to have better detection. This project aimed to study trends of feature selection in IDS and to implement BGSA for selectively choose features for IDS and to test and validate the performance and feedback of BGSA. The significance of feature selection can be viewed in two aspects. First is to filter out noise and remove redundant and irrelevant features and over load of features which causes significant loss of accuracy and time consumption in detection. In this project, it validates and evaluates the BGSA algorithm and focuses on the feature selection by implementing of BGSA. The results of BGSA program proves that the selected features which proposed by BGSA in terms of accuracy and efficiency are quite acceptable. The comparison of classification rates for all the five classes with other approaches which are using the same dataset shows that the BGSA is more accurate than others. 2013-01 Thesis http://eprints.utm.my/id/eprint/33183/ http://eprints.utm.my/id/eprint/33183/5/VahidKavianiJabaliMFSKSM2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Jabali, Vahid Kaviani Gravitational search algorithm for feature selection in intrusion detection system
description	This project was carried out to use the Gravitational Search Algorithm for feature selection in IDS to selectively choose significant features which represents categories of network such as DoS, Probe, U2R and R2L and to improve the accuracy and effectiveness of feature selection and to have better detection. This project aimed to study trends of feature selection in IDS and to implement BGSA for selectively choose features for IDS and to test and validate the performance and feedback of BGSA. The significance of feature selection can be viewed in two aspects. First is to filter out noise and remove redundant and irrelevant features and over load of features which causes significant loss of accuracy and time consumption in detection. In this project, it validates and evaluates the BGSA algorithm and focuses on the feature selection by implementing of BGSA. The results of BGSA program proves that the selected features which proposed by BGSA in terms of accuracy and efficiency are quite acceptable. The comparison of classification rates for all the five classes with other approaches which are using the same dataset shows that the BGSA is more accurate than others.
format	Thesis
qualification_level	Master's degree
author	Jabali, Vahid Kaviani
author_facet	Jabali, Vahid Kaviani
author_sort	Jabali, Vahid Kaviani
title	Gravitational search algorithm for feature selection in intrusion detection system
title_short	Gravitational search algorithm for feature selection in intrusion detection system
title_full	Gravitational search algorithm for feature selection in intrusion detection system
title_fullStr	Gravitational search algorithm for feature selection in intrusion detection system
title_full_unstemmed	Gravitational search algorithm for feature selection in intrusion detection system
title_sort	gravitational search algorithm for feature selection in intrusion detection system
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2013
url	http://eprints.utm.my/id/eprint/33183/5/VahidKavianiJabaliMFSKSM2013.pdf
_version_	1747816099409297408

Gravitational search algorithm for feature selection in intrusion detection system

Similar Items