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Deduplicated Disk Image Evidence Acquisition and Forensically-Sound Reconstruction
Author(s)
Date Issued
2018-08-03
Date Available
2023-11-28T16:04:44Z
Abstract
The ever-growing backlog of digital evidence waiting for analysis has become a significant issue for law enforcement agencies throughout the world. This is due to an increase in the number of cases requiring digital forensic analysis coupled with the increasing volume of data to process per case. This has created a demand for a paradigm shift in the method that evidence is acquired, stored, and analyzed. The ultimate goal of the research presented in this paper is to revolutionize the current digital forensic process through the leveraging of centralized deduplicated acquisition and processing approach. Focusing on this first step in digital evidence processing, acquisition, a system is presented enabling deduplicated evidence acquisition with the capability of automated, forensically-sound complete disk image reconstruction. As the number of cases acquired by the proposed system increases, the more duplicate artifacts will be encountered, and the more efficient the processing of each new case will become. This results in a time saving for digital investigators, and provides a platform to enable non-expert evidence processing, alongside the benefits of reduced storage and bandwidth requirements.
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2018 IEEE
Language
English
Status of Item
Peer reviewed
Journal
2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE)
Conference Details
The 17th IEEE International Conference on Trust, Security and Privacy in Computing and Communication (TustCom), New York, United States of America, 1-3 August 2018
ISBN
9781538643877
ISSN
2324-9013
This item is made available under a Creative Commons License
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Name
ForensicallySoundReconstruction.pdf
Size
347.35 KB
Format
Adobe PDF
Checksum (MD5)
74cd1e9972ab1582bad85c8e4d2d2295
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