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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Forensic Analysis using Text Clustering in the Age of Large Volume Data: A Review

Author 1: Bandar Almaslukh

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2019.0100610

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 6, 2019.

  • Abstract and Keywords
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Abstract: Exploring digital devices in order to generate digital evidence related to an incident being investigated is essential in modern digital investigation. The emergence of text clustering methods plays an important role in developing effective digital forensics techniques. However, the issue of increasing the number of text sources and the volume of digital devices seized for analysis has been raised significantly over the years. Many studies indicated that this issue should be resolved urgently. In this paper, a comprehensive review of digital forensic analysis using text-clustering methods is presented, investigating the challenges of large volume data on digital forensic techniques. Moreover, a meaningful classification and comparison of the text clustering methods that have been frequently used for forensic analysis are provided. The major challenges with solutions and future research directions are also highlighted to open the door for researchers in the area of digital forensics in the age of large volume data.

Keywords: Digital investigation; forensic analysis; text clustering

Bandar Almaslukh, “Forensic Analysis using Text Clustering in the Age of Large Volume Data: A Review” International Journal of Advanced Computer Science and Applications(IJACSA), 10(6), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100610

@article{Almaslukh2019,
title = {Forensic Analysis using Text Clustering in the Age of Large Volume Data: A Review},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100610},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100610},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {6},
author = {Bandar Almaslukh}
}


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