An intelligence technique for denial of service (DoS) attack detection

The emergent damage to computer network keeps increasing due to an extensive and prevalent connectivity on the Internet. Nowadays, attack detection strategies have become the most vital component in computer security despite the main preventive measure in detecting the attacks. The main issue with c...

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Main Authors:	Wan Nurulsafawati, Wan Manan, Tuan Muhammad, Safiuddin, Zarina, Dzolkhifli, Mohd Hafiz, Mohd Hassin
Format:	Article
Language:	English
Published:	American Scientific Publisher 2018
Subjects:	QA76 Computer software
Online Access:	http://umpir.ump.edu.my/id/eprint/21010/ http://umpir.ump.edu.my/id/eprint/21010/ http://umpir.ump.edu.my/id/eprint/21010/ http://umpir.ump.edu.my/id/eprint/21010/1/27.%20An%20Intelligence%20Technique%20For%20Denial%20Of%20Service%20%28Dos%29%20Attack%20Detection1.pdf

id	ump-21010
recordtype	eprints
spelling	ump-210102018-11-12T08:27:41Z http://umpir.ump.edu.my/id/eprint/21010/ An intelligence technique for denial of service (DoS) attack detection Wan Nurulsafawati, Wan Manan Tuan Muhammad, Safiuddin Zarina, Dzolkhifli Mohd Hafiz, Mohd Hassin QA76 Computer software The emergent damage to computer network keeps increasing due to an extensive and prevalent connectivity on the Internet. Nowadays, attack detection strategies have become the most vital component in computer security despite the main preventive measure in detecting the attacks. The main issue with current detection systems is the inability to detect the malicious activity in certain circumstances. Most of the current intrusion detection systems implemented nowadays depend on expert systems where new attacks are not detectable. Therefore, this paper concern about Denial of Service (DoS) attack, detection using Neural Network. The data used in training and testing was KDD 99 data set based on the Defense Advanced Research Projects Agency (DARPA) intrusion detection programme, which is publicly accessible by Lincoln Labs. Special features of connection records have been acknowledged to be used in DoS attacks. The result from this experiment will show the effectiveness of Neural Network using the backpropagation learning algorithm for detecting DoS attack. American Scientific Publisher 2018 Article PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/21010/1/27.%20An%20Intelligence%20Technique%20For%20Denial%20Of%20Service%20%28Dos%29%20Attack%20Detection1.pdf Wan Nurulsafawati, Wan Manan and Tuan Muhammad, Safiuddin and Zarina, Dzolkhifli and Mohd Hafiz, Mohd Hassin (2018) An intelligence technique for denial of service (DoS) attack detection. Advanced Science Letters, 24 (10). pp. 7446-7450. ISSN 1936-6612 https://doi.org/10.1166/asl.2018.12956 DOI: 10.1166/asl.2018.12956
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	QA76 Computer software
spellingShingle	QA76 Computer software Wan Nurulsafawati, Wan Manan Tuan Muhammad, Safiuddin Zarina, Dzolkhifli Mohd Hafiz, Mohd Hassin An intelligence technique for denial of service (DoS) attack detection
description	The emergent damage to computer network keeps increasing due to an extensive and prevalent connectivity on the Internet. Nowadays, attack detection strategies have become the most vital component in computer security despite the main preventive measure in detecting the attacks. The main issue with current detection systems is the inability to detect the malicious activity in certain circumstances. Most of the current intrusion detection systems implemented nowadays depend on expert systems where new attacks are not detectable. Therefore, this paper concern about Denial of Service (DoS) attack, detection using Neural Network. The data used in training and testing was KDD 99 data set based on the Defense Advanced Research Projects Agency (DARPA) intrusion detection programme, which is publicly accessible by Lincoln Labs. Special features of connection records have been acknowledged to be used in DoS attacks. The result from this experiment will show the effectiveness of Neural Network using the backpropagation learning algorithm for detecting DoS attack.
format	Article
author	Wan Nurulsafawati, Wan Manan Tuan Muhammad, Safiuddin Zarina, Dzolkhifli Mohd Hafiz, Mohd Hassin
author_facet	Wan Nurulsafawati, Wan Manan Tuan Muhammad, Safiuddin Zarina, Dzolkhifli Mohd Hafiz, Mohd Hassin
author_sort	Wan Nurulsafawati, Wan Manan
title	An intelligence technique for denial of service (DoS) attack detection
title_short	An intelligence technique for denial of service (DoS) attack detection
title_full	An intelligence technique for denial of service (DoS) attack detection
title_fullStr	An intelligence technique for denial of service (DoS) attack detection
title_full_unstemmed	An intelligence technique for denial of service (DoS) attack detection
title_sort	intelligence technique for denial of service (dos) attack detection
publisher	American Scientific Publisher
publishDate	2018
url	http://umpir.ump.edu.my/id/eprint/21010/ http://umpir.ump.edu.my/id/eprint/21010/ http://umpir.ump.edu.my/id/eprint/21010/ http://umpir.ump.edu.my/id/eprint/21010/1/27.%20An%20Intelligence%20Technique%20For%20Denial%20Of%20Service%20%28Dos%29%20Attack%20Detection1.pdf
first_indexed	2023-09-18T22:30:39Z
last_indexed	2023-09-18T22:30:39Z
_version_	1777416262968672256

An intelligence technique for denial of service (DoS) attack detection

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