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DDoS Classification using Combined Techniques

Now-a-days, the attacker's favourite is to disrupt a network system. An attacker has the capability to generate various types of DDoS attacks simultaneously, including the Smurf attack, ICMP flood, UDP flood, and TCP SYN flood. This DDoS issue encouraged the design of a classification techn...

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Main Authors:	Mohd Yusof, Mohd Azahari, Mohd Safar, Noor Zuraidin, Abdullah, Zubaile, Hamid Ali, Firkhan Ali, Mohamad Sukri, Khairul Amin, Jofri, Muhamad Hanif, Mohamed, Juliana, Omar, Abdul Halim, Bahrudin, Ida Aryanie, Mohamed Ali @ Md Hani, Mohd Hatta
Format:	Article
Language:	English
Published:	ijacsa 2024
Subjects:	T Technology (General)
Online Access:	http://eprints.uthm.edu.my/10936/1/J17424_0b14450bdb1b1d7104fe305c68705989.pdf http://eprints.uthm.edu.my/10936/
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id	my.uthm.eprints.10936
record_format	eprints
spelling	my.uthm.eprints.109362024-05-13T11:51:09Z http://eprints.uthm.edu.my/10936/ DDoS Classification using Combined Techniques Mohd Yusof, Mohd Azahari Mohd Safar, Noor Zuraidin Abdullah, Zubaile Hamid Ali, Firkhan Ali Mohamad Sukri, Khairul Amin Jofri, Muhamad Hanif Mohamed, Juliana Omar, Abdul Halim Bahrudin, Ida Aryanie Mohamed Ali @ Md Hani, Mohd Hatta T Technology (General) Now-a-days, the attacker's favourite is to disrupt a network system. An attacker has the capability to generate various types of DDoS attacks simultaneously, including the Smurf attack, ICMP flood, UDP flood, and TCP SYN flood. This DDoS issue encouraged the design of a classification technique against DDoS attacks that enter a computer network environment. The technique is called Packet Threshold Algorithm (PTA) and is combined with several machine learning to classify incoming packets that have been captured and recorded. Apart from that, the combination of techniques can differentiate between normal packets and DDoS attacks. The performance of all techniques in the research achieved high detection accuracy while mitigating the issue of a high false positive rate. The four techniques focused in this research are PTA-SVM, PTA-NB, PTA-LR and PTA-KNN. Based on the results of detection accuracy and false positive rate for all the techniques involved, it proves the PTA-KNN technique is a more effective technique in the context of detection of incoming packets whether DDoS attacks or normal packets ijacsa 2024 Article PeerReviewed text en http://eprints.uthm.edu.my/10936/1/J17424_0b14450bdb1b1d7104fe305c68705989.pdf Mohd Yusof, Mohd Azahari and Mohd Safar, Noor Zuraidin and Abdullah, Zubaile and Hamid Ali, Firkhan Ali and Mohamad Sukri, Khairul Amin and Jofri, Muhamad Hanif and Mohamed, Juliana and Omar, Abdul Halim and Bahrudin, Ida Aryanie and Mohamed Ali @ Md Hani, Mohd Hatta (2024) DDoS Classification using Combined Techniques. International Journal of Advanced Computer Science and Applications, 15 (1). pp. 551-557.
institution	Universiti Tun Hussein Onn Malaysia
building	UTHM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Tun Hussein Onn Malaysia
content_source	UTHM Institutional Repository
url_provider	http://eprints.uthm.edu.my/
language	English
topic	T Technology (General)
spellingShingle	T Technology (General) Mohd Yusof, Mohd Azahari Mohd Safar, Noor Zuraidin Abdullah, Zubaile Hamid Ali, Firkhan Ali Mohamad Sukri, Khairul Amin Jofri, Muhamad Hanif Mohamed, Juliana Omar, Abdul Halim Bahrudin, Ida Aryanie Mohamed Ali @ Md Hani, Mohd Hatta DDoS Classification using Combined Techniques
description	Now-a-days, the attacker's favourite is to disrupt a network system. An attacker has the capability to generate various types of DDoS attacks simultaneously, including the Smurf attack, ICMP flood, UDP flood, and TCP SYN flood. This DDoS issue encouraged the design of a classification technique against DDoS attacks that enter a computer network environment. The technique is called Packet Threshold Algorithm (PTA) and is combined with several machine learning to classify incoming packets that have been captured and recorded. Apart from that, the combination of techniques can differentiate between normal packets and DDoS attacks. The performance of all techniques in the research achieved high detection accuracy while mitigating the issue of a high false positive rate. The four techniques focused in this research are PTA-SVM, PTA-NB, PTA-LR and PTA-KNN. Based on the results of detection accuracy and false positive rate for all the techniques involved, it proves the PTA-KNN technique is a more effective technique in the context of detection of incoming packets whether DDoS attacks or normal packets
format	Article
author	Mohd Yusof, Mohd Azahari Mohd Safar, Noor Zuraidin Abdullah, Zubaile Hamid Ali, Firkhan Ali Mohamad Sukri, Khairul Amin Jofri, Muhamad Hanif Mohamed, Juliana Omar, Abdul Halim Bahrudin, Ida Aryanie Mohamed Ali @ Md Hani, Mohd Hatta
author_facet	Mohd Yusof, Mohd Azahari Mohd Safar, Noor Zuraidin Abdullah, Zubaile Hamid Ali, Firkhan Ali Mohamad Sukri, Khairul Amin Jofri, Muhamad Hanif Mohamed, Juliana Omar, Abdul Halim Bahrudin, Ida Aryanie Mohamed Ali @ Md Hani, Mohd Hatta
author_sort	Mohd Yusof, Mohd Azahari
title	DDoS Classification using Combined Techniques
title_short	DDoS Classification using Combined Techniques
title_full	DDoS Classification using Combined Techniques
title_fullStr	DDoS Classification using Combined Techniques
title_full_unstemmed	DDoS Classification using Combined Techniques
title_sort	ddos classification using combined techniques
publisher	ijacsa
publishDate	2024
url	http://eprints.uthm.edu.my/10936/1/J17424_0b14450bdb1b1d7104fe305c68705989.pdf http://eprints.uthm.edu.my/10936/
_version_	1800094628495491072
score	13.211869

DDoS Classification using Combined Techniques

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