Integrated examination and analysis model for improving mobile cloud forensic investigation

Advanced forensic techniques become inevitable to investigate the malicious activities in Cloud-based Mobile Applications (CMA). It is challenging to analyse the casespecific evidential artifact from the Mobile Cloud Computing (MCC) environment under forensically sound conditions. The Mobile Cloud I...

Full description

Saved in:

Bibliographic Details
Main Author:	Alnajjar, Ibrahim Ali Mohammad
Format:	Thesis
Language:	eng eng
Published:	2022
Subjects:	QA299.6-433 Analysis
Online Access:	https://etd.uum.edu.my/10209/1/s902016_01.pdf https://etd.uum.edu.my/10209/2/s902016_02.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-uum-etd.10209
record_format	uketd_dc
spelling	my-uum-etd.102092023-01-11T00:20:46Z Integrated examination and analysis model for improving mobile cloud forensic investigation 2022 Alnajjar, Ibrahim Ali Mohammad Mahmuddin, Massudi Awang Had Salleh Graduate School of Arts & Sciences Awang Had Salleh Graduate School of Arts and Sciences QA299.6-433 Analysis Advanced forensic techniques become inevitable to investigate the malicious activities in Cloud-based Mobile Applications (CMA). It is challenging to analyse the casespecific evidential artifact from the Mobile Cloud Computing (MCC) environment under forensically sound conditions. The Mobile Cloud Investigation (MCI) encounters many research issues in tracing and fine-tuning the relevant evidential artifacts from the MCC environment. This research proposes an integrated Examination and Analysis (EA) model for a generalised application architecture of CMA deployable on the public cloud to trace the case-specific evidential artifacts. The proposed model effectively validates MCI and enhances the accuracy and speed of the investigation. In this context, proposing Forensic Examination and Analysis Methodology using Data mining (FED) and Forensic Examination and analysis methodology using Data mining and Optimization (FEDO) models address these issues. The FED incorporates key sub-phases such as timeline analysis, hash filtering, data carving, and data transformation to filter out case-specific artifacts. The Long Short-Term Memory (LSTM) assisted forensic methodology decides the amount of potential information to be retained for further investigation and categorizes the forensic evidential artifacts for the relevancy of the crime event. Finally, the FED model constructs the forensic evidence taxonomy and maintains the precision and recall above 85% for effective decision-making. FEDO facilitates cloud evidence by examining the key features and indexing the evidence. The FEDO incorporates several sub-phases to precisely handle the evidence, such as evidence indexing, crossreferencing, and keyword searching. It analyses the temporal and geographic information and performs cross-referencing to fine-tune the evidence towards the casespecific evidence. FEDO models the Linearly Decreasing Weight (LDW) strategy based Particle Swarm Optimization (PSO) algorithm on the case-specific evidence to improve the searching capability of the investigation across the massive MCC environment. FEDO delivers the evidence tracing rate at 90%, and thus the integrated EA ensures improved MCI performance. 2022 Thesis https://etd.uum.edu.my/10209/ https://etd.uum.edu.my/10209/1/s902016_01.pdf text eng 2024-09-05 staffonly https://etd.uum.edu.my/10209/2/s902016_02.pdf text eng public phd doctoral Universiti Utara Malaysia
institution	Universiti Utara Malaysia
collection	UUM ETD
language	eng eng
advisor	Mahmuddin, Massudi
topic	QA299.6-433 Analysis
spellingShingle	QA299.6-433 Analysis Alnajjar, Ibrahim Ali Mohammad Integrated examination and analysis model for improving mobile cloud forensic investigation
description	Advanced forensic techniques become inevitable to investigate the malicious activities in Cloud-based Mobile Applications (CMA). It is challenging to analyse the casespecific evidential artifact from the Mobile Cloud Computing (MCC) environment under forensically sound conditions. The Mobile Cloud Investigation (MCI) encounters many research issues in tracing and fine-tuning the relevant evidential artifacts from the MCC environment. This research proposes an integrated Examination and Analysis (EA) model for a generalised application architecture of CMA deployable on the public cloud to trace the case-specific evidential artifacts. The proposed model effectively validates MCI and enhances the accuracy and speed of the investigation. In this context, proposing Forensic Examination and Analysis Methodology using Data mining (FED) and Forensic Examination and analysis methodology using Data mining and Optimization (FEDO) models address these issues. The FED incorporates key sub-phases such as timeline analysis, hash filtering, data carving, and data transformation to filter out case-specific artifacts. The Long Short-Term Memory (LSTM) assisted forensic methodology decides the amount of potential information to be retained for further investigation and categorizes the forensic evidential artifacts for the relevancy of the crime event. Finally, the FED model constructs the forensic evidence taxonomy and maintains the precision and recall above 85% for effective decision-making. FEDO facilitates cloud evidence by examining the key features and indexing the evidence. The FEDO incorporates several sub-phases to precisely handle the evidence, such as evidence indexing, crossreferencing, and keyword searching. It analyses the temporal and geographic information and performs cross-referencing to fine-tune the evidence towards the casespecific evidence. FEDO models the Linearly Decreasing Weight (LDW) strategy based Particle Swarm Optimization (PSO) algorithm on the case-specific evidence to improve the searching capability of the investigation across the massive MCC environment. FEDO delivers the evidence tracing rate at 90%, and thus the integrated EA ensures improved MCI performance.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Alnajjar, Ibrahim Ali Mohammad
author_facet	Alnajjar, Ibrahim Ali Mohammad
author_sort	Alnajjar, Ibrahim Ali Mohammad
title	Integrated examination and analysis model for improving mobile cloud forensic investigation
title_short	Integrated examination and analysis model for improving mobile cloud forensic investigation
title_full	Integrated examination and analysis model for improving mobile cloud forensic investigation
title_fullStr	Integrated examination and analysis model for improving mobile cloud forensic investigation
title_full_unstemmed	Integrated examination and analysis model for improving mobile cloud forensic investigation
title_sort	integrated examination and analysis model for improving mobile cloud forensic investigation
granting_institution	Universiti Utara Malaysia
granting_department	Awang Had Salleh Graduate School of Arts & Sciences
publishDate	2022
url	https://etd.uum.edu.my/10209/1/s902016_01.pdf https://etd.uum.edu.my/10209/2/s902016_02.pdf
_version_	1776103766425075712

Integrated examination and analysis model for improving mobile cloud forensic investigation

Similar Items