Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks

This thesis proposes an approach to detect HTTP flooding DDoS attacks on web servers. The proposed approach consists of five phases to achieve the goal of the research, as follows: (1) Data pre-processing, (ii) Aggregated packets attributes aim to aggregate the packets every (t) time based on three...

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Main Author:	Ghaben, Ayman Ibrahim Ali
Format:	Thesis
Language:	English
Published:	2023
Subjects:	T1-995 Technology(General)
Online Access:	http://eprints.usm.my/60176/1/Pages%20from%20AYMAN%20IBRAHIM%20ALI%20GHABEN%20-%20TESIS.pdf
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id	my-usm-ep.60176
record_format	uketd_dc
spelling	my-usm-ep.601762024-03-13T07:40:08Z Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks 2023-01 Ghaben, Ayman Ibrahim Ali T1-995 Technology(General) This thesis proposes an approach to detect HTTP flooding DDoS attacks on web servers. The proposed approach consists of five phases to achieve the goal of the research, as follows: (1) Data pre-processing, (ii) Aggregated packets attributes aim to aggregate the packets every (t) time based on three attributes which are (a) packet size, (b) regularity (inter arrival time), and (c) number of packets (iii) Anomaly-based detection using four indicators which are : (a) summation rows-columns, (b) Bayes- entropy, (c) skew of the packets distribution, and (d) Reynolds number) (iv) voting- based mechanism, and (v) statistical based mechanism. The proposed mechanism has been evaluated using two benchmark datasets (CIC DDoS and ISCX) and the results reveal that the detection accuracy rates are 96.03% and 94.28% when evaluated over CIC DDoS and ISCX datasets, respectively. Furthermore, the false positive rates are 14.28%, 10.00% when evaluated over those datasets. 2023-01 Thesis http://eprints.usm.my/60176/ http://eprints.usm.my/60176/1/Pages%20from%20AYMAN%20IBRAHIM%20ALI%20GHABEN%20-%20TESIS.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat IPv6 Termaju Negara (National Advanced IPv6 Centre of Excellence NAv6)
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	T1-995 Technology(General)
spellingShingle	T1-995 Technology(General) Ghaben, Ayman Ibrahim Ali Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks
description	This thesis proposes an approach to detect HTTP flooding DDoS attacks on web servers. The proposed approach consists of five phases to achieve the goal of the research, as follows: (1) Data pre-processing, (ii) Aggregated packets attributes aim to aggregate the packets every (t) time based on three attributes which are (a) packet size, (b) regularity (inter arrival time), and (c) number of packets (iii) Anomaly-based detection using four indicators which are : (a) summation rows-columns, (b) Bayes- entropy, (c) skew of the packets distribution, and (d) Reynolds number) (iv) voting- based mechanism, and (v) statistical based mechanism. The proposed mechanism has been evaluated using two benchmark datasets (CIC DDoS and ISCX) and the results reveal that the detection accuracy rates are 96.03% and 94.28% when evaluated over CIC DDoS and ISCX datasets, respectively. Furthermore, the false positive rates are 14.28%, 10.00% when evaluated over those datasets.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Ghaben, Ayman Ibrahim Ali
author_facet	Ghaben, Ayman Ibrahim Ali
author_sort	Ghaben, Ayman Ibrahim Ali
title	Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks
title_short	Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks
title_full	Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks
title_fullStr	Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks
title_full_unstemmed	Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks
title_sort	statistical-based mechanism for detecting hyper text transfer protocol ddos attacks
granting_institution	Universiti Sains Malaysia
granting_department	Pusat IPv6 Termaju Negara (National Advanced IPv6 Centre of Excellence NAv6)
publishDate	2023
url	http://eprints.usm.my/60176/1/Pages%20from%20AYMAN%20IBRAHIM%20ALI%20GHABEN%20-%20TESIS.pdf
_version_	1794024100493000704

Statistical-Based Mechanism For Detecting Hyper Text Transfer Protocol Ddos Attacks

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