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Advances in Digital Forensics Frameworks and Tools: A Comparative Insight and Ranking

Advances in Digital Forensics Frameworks and Tools: A Comparative Insight and Ranking

Muhammad Abulaish, Nur Al Hasan Haldar
Copyright: © 2018 |Volume: 10 |Issue: 2 |Pages: 25
ISSN: 1941-6210|EISSN: 1941-6229|EISBN13: 9781522543619|DOI: 10.4018/IJDCF.2018040106
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MLA

Abulaish, Muhammad, and Nur Al Hasan Haldar. "Advances in Digital Forensics Frameworks and Tools: A Comparative Insight and Ranking." IJDCF vol.10, no.2 2018: pp.95-119. http://doi.org/10.4018/IJDCF.2018040106

APA

Abulaish, M. & Haldar, N. A. (2018). Advances in Digital Forensics Frameworks and Tools: A Comparative Insight and Ranking. International Journal of Digital Crime and Forensics (IJDCF), 10(2), 95-119. http://doi.org/10.4018/IJDCF.2018040106

Chicago

Abulaish, Muhammad, and Nur Al Hasan Haldar. "Advances in Digital Forensics Frameworks and Tools: A Comparative Insight and Ranking," International Journal of Digital Crime and Forensics (IJDCF) 10, no.2: 95-119. http://doi.org/10.4018/IJDCF.2018040106

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Abstract

Digital forensics science is a well-known initiative to unearth computer-assisted crimes. The thriving criminal activities using digital media have changed the typical definition of a traditional crime. Meanwhile, the means and targets of criminal activities have been transformed in a broader context due to the diverse nature of offenses associated with the multiple crime categories, affecting the way of investigations as well. In order to withstand the difficulties caused due to the crime complexity, forensics investigation frameworks are being tuned to adjust with the nature and earnestness of the felonies being committed. This article presents an in-depth comparative survey of fourteen popular and most cited digital forensics process models and various forensics tools associated with different phases of these models. The relationships among these forensics process models and their evolutions are analyzed and a graph-theoretic approach is presented to rank the existing process models to facilitate investigators in selecting an appropriate model for their investigation tasks.

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