Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event

The goal of the thesis is to propose an approach that can detect flash crowd attacks that target web servers during flash events. The proposed approach consists of four phases to achieve the goal of the research. The proposed approach is evaluated using three different datasets distributed in three...

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Main Author: Al-Saleem, Samer Abdulsada Mutlag
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://eprints.usm.my/47734/1/ANOMALY-BASED%20DETECTION%20APPROACH%20TO.pdf%20cut.pdf
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id my-usm-ep.47734
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spelling my-usm-ep.477342020-10-23T08:57:06Z Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event 2017-12 Al-Saleem, Samer Abdulsada Mutlag TK5105 Computer networks and Data transmission systems The goal of the thesis is to propose an approach that can detect flash crowd attacks that target web servers during flash events. The proposed approach consists of four phases to achieve the goal of the research. The proposed approach is evaluated using three different datasets distributed in three scenarios. The first scenario is aimed to validate the detection accuracy of the proposed approach when a web server is in a normal situation (when there is no threat targeting the server). The second scenario (flash event dataset) is aimed to improve the accuracy of the proposed approach in detecting anomalous behaviour when the server is facing a flash event. The third scenario (flash crowd attack dataset) is aimed to verify and validate the accuracy of the proposed approach in terms of detecting the flash crowd attack that targets the web server during the flash event. 2017-12 Thesis http://eprints.usm.my/47734/ http://eprints.usm.my/47734/1/ANOMALY-BASED%20DETECTION%20APPROACH%20TO.pdf%20cut.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 TK5105 Computer networks and Data transmission systems
spellingShingle TK5105 Computer networks and Data transmission systems
Al-Saleem, Samer Abdulsada Mutlag
Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event
description The goal of the thesis is to propose an approach that can detect flash crowd attacks that target web servers during flash events. The proposed approach consists of four phases to achieve the goal of the research. The proposed approach is evaluated using three different datasets distributed in three scenarios. The first scenario is aimed to validate the detection accuracy of the proposed approach when a web server is in a normal situation (when there is no threat targeting the server). The second scenario (flash event dataset) is aimed to improve the accuracy of the proposed approach in detecting anomalous behaviour when the server is facing a flash event. The third scenario (flash crowd attack dataset) is aimed to verify and validate the accuracy of the proposed approach in terms of detecting the flash crowd attack that targets the web server during the flash event.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Al-Saleem, Samer Abdulsada Mutlag
author_facet Al-Saleem, Samer Abdulsada Mutlag
author_sort Al-Saleem, Samer Abdulsada Mutlag
title Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event
title_short Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event
title_full Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event
title_fullStr Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event
title_full_unstemmed Anomaly-Based Detection Approach To Detect The Flash Crowd Attack During The Flash Event
title_sort anomaly-based detection approach to detect the flash crowd attack during the flash event
granting_institution Universiti Sains Malaysia
granting_department Pusat IPv6 Termaju Negara (National Advanced IPv6 Centre of Excellence NAv6)
publishDate 2017
url http://eprints.usm.my/47734/1/ANOMALY-BASED%20DETECTION%20APPROACH%20TO.pdf%20cut.pdf
_version_ 1747821821911105536