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  5. Battling the digital forensic backlog through data deduplication
 
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Battling the digital forensic backlog through data deduplication

Author(s)
Scanlon, Mark  
Uri
http://hdl.handle.net/10197/25099
Date Issued
2016-08-26
Date Available
2023-12-04T16:31:43Z
Abstract
In recent years, technology has become truly pervasive in everyday life. Technological advancement can be found in many facets of life, including personal computers, mobile devices, wearables, cloud services, video gaming, web-powered messaging, social media, Internet-connected devices, etc. This technological influence has resulted in these technologies being employed by criminals to conduct a range of crimes - both online and offline. Both the number of cases requiring digital forensic analysis and the sheer volume of information to be processed in each case has increased rapidly in recent years. As a result, the requirement for digital forensic investigation has ballooned, and law enforcement agencies throughout the world are scrambling to address this demand. While more and more members of law enforcement are being trained to perform the required investigations, the supply is not keeping up with the demand. Current digital forensic techniques are arduously time-consuming and require a significant amount of man power to execute. This paper discusses a novel solution to combat the digital forensic backlog. This solution leverages a deduplication-based paradigm to eliminate the reacquisition, redundant storage, and reanalysis of previously processed data.
Type of Material
Conference Publication
Publisher
IEEE
Copyright (Published Version)
2016 IEEE
Subjects

Digital forensics

Databases

Law enforcement

Image reconstruction

Workstations

Cloud computing

DOI
10.1109/INTECH.2016.7845139
Web versions
https://intech.aconf.org
Language
English
Status of Item
Peer reviewed
Journal
2016 6th International Conference on Innovative Computing Technology, INTECH 2016
Conference Details
The 2016 Sixth International Conference on Innovative Computing Technology (INTECH), Dublin, Ireland, 24-26 August 2016
ISBN
9781509020003
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
File(s)
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BattlingTheBacklogDataDeduplication.pdf

Size

531.06 KB

Format

Adobe PDF

Checksum (MD5)

f44fe42e15342936132e1b0c53c8e407

Owning collection
Computer Science Research Collection

Item descriptive metadata is released under a CC-0 (public domain) license: https://creativecommons.org/public-domain/cc0/.
All other content is subject to copyright.

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