Prior Publisher

The Association of Digital Forensics, Security and Law (ADFSL)


In Digital Forensics, the number of person-hours spent on investigation is a key factor which needs to be kept to a minimum whilst also paying close attention to the authenticity of the evidence. The literature describes challenges behind increasing person-hours and identifies several factors which contribute to this phenomenon. This paper reviews these factors and demonstrates that they do not wholly account for increases in investigation time. Using real case records from the Dubai Police, an extensive study explains the contribution of other factors to the increase in person-hours. We conclude this work by emphasizing on several factors affecting the person-hours in contrast to what most of the literature in this area proposes.


Irons, A., & Lallie, H. S. (2014). Digital Forensics to Intelligent Forensics. Future Internet, 6(3), 584-596.

Gogolin, G. (2010). The Digital Crime Tsunami. Digital Investigation, 7(1–2), 3-8. doi: http://dx.doi.org/10.1016/j.diin.2010.07.001

Dezfoli, F. N., Dehghantanha, A., Mahmoud, R., Sani, N. F. B. M., & Daryabar, F. (2013). Digital Forensic Trends and Future. International Journal of Cyber-Security and Digital Forensics (IJCSDF), 2(2), 48-76.

Roy, M. B. (2014). An analysis of the applicability of federal law regarding hash-based searches of digital media. Monterey, California: Naval Postgraduate School.

James, J. I. (2014). Multi-Stakeholder Case Prioritization in Digital Investigations. Journal of Digital Forensics, Security and Law, 9(2), 59-72.

Shaw, A., & Browne, A. (2013). A practical and robust approach to coping with large volumes of data submitted for digital forensic examination. Digital Investigation, 10(2), 116-128.

Prefuse. (2013). the prefuse visualization toolkit. from http://prefuse.org/

Roussev, V., Richard, G. Breaking the Performance Wall: The Case for Distributed Digital Forensics. In Proceedings of the 2004 Digital Forensics Research Workshop (DFRWS). Aug 2004, Baltimore, MD

Nirkhi, S. M., Dharaskar, R., & Thakre, V. (2012). Data Mining: A Prospective Approach for Digital Forensics. International Journal of Data Mining & Knowledge Management Process, 2(6), 45.

Kim, C. (1996). Cook's distance in spline smoothing. Statistics & probability letters, 31(2), 139-144.



To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.