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 Nurul Safawati, Wan Manan, Tuan Muhammad, Safiuddin
Format:	Conference or Workshop Item
Language:	English
Published:	2017
Subjects:	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/19605/ http://umpir.ump.edu.my/id/eprint/19605/ http://umpir.ump.edu.my/id/eprint/19605/1/An%20Intelligence%20Technique%20For%20Denial%20Of%20Service%20%28Dos%29%20Attack%20Detection.pdf

id	ump-19605
recordtype	eprints
spelling	ump-196052018-02-20T07:22:10Z http://umpir.ump.edu.my/id/eprint/19605/ An Intelligence Technique For Denial Of Service (Dos) Attack Detection Wan Nurul Safawati, Wan Manan Tuan Muhammad, Safiuddin QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering 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. 2017-11 Conference or Workshop Item NonPeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/19605/1/An%20Intelligence%20Technique%20For%20Denial%20Of%20Service%20%28Dos%29%20Attack%20Detection.pdf Wan Nurul Safawati, Wan Manan and Tuan Muhammad, Safiuddin (2017) An Intelligence Technique For Denial Of Service (Dos) Attack Detection. In: The 5th International Conference on Software Engineering & Computer System ( ICSECS' 17), 22-24 November 2017 , Adya Hotel, Pulau Langkawi, Malaysia. p. 1.. (Unpublished) http://icsecs.ump.edu.my/index.php/en/#
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 TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	QA76 Computer software TK Electrical engineering. Electronics Nuclear engineering Wan Nurul Safawati, Wan Manan Tuan Muhammad, Safiuddin 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	Conference or Workshop Item
author	Wan Nurul Safawati, Wan Manan Tuan Muhammad, Safiuddin
author_facet	Wan Nurul Safawati, Wan Manan Tuan Muhammad, Safiuddin
author_sort	Wan Nurul Safawati, 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
publishDate	2017
url	http://umpir.ump.edu.my/id/eprint/19605/ http://umpir.ump.edu.my/id/eprint/19605/ http://umpir.ump.edu.my/id/eprint/19605/1/An%20Intelligence%20Technique%20For%20Denial%20Of%20Service%20%28Dos%29%20Attack%20Detection.pdf
first_indexed	2023-09-18T22:28:02Z
last_indexed	2023-09-18T22:28:02Z
_version_	1777416098692464640

An Intelligence Technique For Denial Of Service (Dos) Attack Detection

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