Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics

The increasing number of cyber crimes has motivated network forensics researchers to develop new techniques to analyze and investigate these crimes. Although cyber crimes produce a large volume of evidence, analyzing and measuring the extent of the damages caused by these crimes are difficult becaus...

Full description

Saved in:

Bibliographic Details
Main Author:	Mosa, Mohammad Rasmi Hassun
Format:	Thesis
Language:	English
Published:	2013
Subjects:	QA75.5-76.95 Electronic computers Computer science
Online Access:	http://eprints.usm.my/43822/1/Mohammad%20Rasmi%20Hassun%20Mosa24.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-usm-ep.43822
record_format	uketd_dc
spelling	my-usm-ep.438222019-04-12T05:26:13Z Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics 2013-06 Mosa, Mohammad Rasmi Hassun QA75.5-76.95 Electronic computers. Computer science The increasing number of cyber crimes has motivated network forensics researchers to develop new techniques to analyze and investigate these crimes. Although cyber crimes produce a large volume of evidence, analyzing and measuring the extent of the damages caused by these crimes are difficult because of the overwhelming amount of evidence involved in each case. Thus, current cyber crime investigation techniques are costly and time consuming. In addition, these techniques normally use active and reactive processes to analyze cyber crimes, and such processes start after the cyber crime has been identified, which makes identifying useful evidence difficult. Moreover, the information required to understand and analyze cyber crime factors such as the intention and strategy of the crime are limited. This thesis proposes a new framework to analyze cyber crime evidence. The proposed framework aims to use cyber crime evidence to reconstruct attack intentions and estimate similar attack strategies. The intentions are identified through a new algorithm called Attack Intention Analysis, which predicts cyber crime intentions by combining Dempster-Shafer theory and a causal network. Similar attack strategies have been estimated by using one of the two proposed methods. The first method creates a new model that uses evidence when the intentions for a cyber crime are undetected. This model aims to measure similar evidence between new and pre-existing cyber crime cases to estimate similar strategies. 2013-06 Thesis http://eprints.usm.my/43822/ http://eprints.usm.my/43822/1/Mohammad%20Rasmi%20Hassun%20Mosa24.pdf application/pdf en public phd doctoral Universiti Sains Malaysia Pusat Pengajian Sains Komputer
institution	Universiti Sains Malaysia
collection	USM Institutional Repository
language	English
topic	QA75.5-76.95 Electronic computers Computer science
spellingShingle	QA75.5-76.95 Electronic computers Computer science Mosa, Mohammad Rasmi Hassun Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
description	The increasing number of cyber crimes has motivated network forensics researchers to develop new techniques to analyze and investigate these crimes. Although cyber crimes produce a large volume of evidence, analyzing and measuring the extent of the damages caused by these crimes are difficult because of the overwhelming amount of evidence involved in each case. Thus, current cyber crime investigation techniques are costly and time consuming. In addition, these techniques normally use active and reactive processes to analyze cyber crimes, and such processes start after the cyber crime has been identified, which makes identifying useful evidence difficult. Moreover, the information required to understand and analyze cyber crime factors such as the intention and strategy of the crime are limited. This thesis proposes a new framework to analyze cyber crime evidence. The proposed framework aims to use cyber crime evidence to reconstruct attack intentions and estimate similar attack strategies. The intentions are identified through a new algorithm called Attack Intention Analysis, which predicts cyber crime intentions by combining Dempster-Shafer theory and a causal network. Similar attack strategies have been estimated by using one of the two proposed methods. The first method creates a new model that uses evidence when the intentions for a cyber crime are undetected. This model aims to measure similar evidence between new and pre-existing cyber crime cases to estimate similar strategies.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Mosa, Mohammad Rasmi Hassun
author_facet	Mosa, Mohammad Rasmi Hassun
author_sort	Mosa, Mohammad Rasmi Hassun
title	Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
title_short	Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
title_full	Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
title_fullStr	Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
title_full_unstemmed	Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics
title_sort	quantitative computational framework for analyzing evidence to identify attack intention and strategy in network forensics
granting_institution	Universiti Sains Malaysia
granting_department	Pusat Pengajian Sains Komputer
publishDate	2013
url	http://eprints.usm.my/43822/1/Mohammad%20Rasmi%20Hassun%20Mosa24.pdf
_version_	1747821285427118080

Quantitative Computational Framework For Analyzing Evidence To Identify Attack Intention And Strategy In Network Forensics

Similar Items