Case Study Based On Decision Theory And Methodology

Behn, R. D. & Vaupel, J. W. Quick Analysis for Decision Makers. New York, NY: Basic Books, 1982.

Maguire, L. A. Using decision analysis to manage endangered species populations. Journal of Environmental Management22, 345–360 (1986).

Maguire, L. A. & Boiney, L. G. Resolving environmental disputes: A framework incorporating decision analysis and dispute resolution techniques. Journal of Environmental Management42, 31–48 (1994).

Malpica, J. M. & Briscoe, D. A. Effective population number estimates of laboratory populations of Drosophila melanogaster. Experientia37, 947–948 (1981).

National Marine Fisheries Service (NMFS). "Final recovery plan for the Steller sea lion (Eumetopias jubatus)." Prepared by the Steller Sea Lion Recovery Team for NMFS. Silver Spring, MD. 1992.

National Marine Fisheries Service (NMFS). "Status review of Steller sea lions (Eumetopias jubatus)." National Marine Mammal Laboratory, Alaska Fisheries Science Center, NMFS, NOAA. 1995.

Raiffa, H. Decision Analysis: Introductory Lectures on Choices under Uncertainty. Boston, MA: Addison-Wesley, 1968.

Ralls, K. & Taylor, B. L. "How viable are population viability analyses?" in The Ecological Basis of Conservation, eds. S. T. A. Pickett et al. New York, NY: Chapman and Hall, 1997.

Resnik, M. D. Choices: An Introduction to Decision Theory. Minneapolis: University of Minnesota Press, 1987.

Possingham, H. et al. Alex 2.2 Operation Manual. Adelaide, Australia: Department of Applied Mathematics, University of Adelaide, 1992.

Possingham, H. P. et al. Metapopulation analysis of the greater glider (Petauroides volans) in a wood production area. Biological Conservation70, 227–236 (1994).

Winkler, R. L. An Introduction to Bayesian Inference and Decision. Gainesville, Florida: Probabilistic Publishing, 1972.


The omnipresence of mobile devices (or small scale digital devices – SSDD) and more importantly the utility of their associated applications for our daily activities, which range from financial transactions to learning, and from entertainment to distributed social presence, create an abundance of digital evidence for each individual. Some of the evidence may be a result of illegal activities that need to be identified, understood and eventually prevented in the future. There are numerous tools for acquiring and analyzing digital evidence extracted from mobile devices. The diversity of SSDDs, types of evidence generated and the number of tools used to uncover them posit a rather complex and challenging problem of selecting the best available tool for the extraction and the subsequent analysis of the evidence gathered from a specific digital device. Failing to select the best tool may easily lead to incomplete and or improper extraction, which eventually may violate the integrity of the digital evidence and diminish its probative value. Moreover, the compromised evidence may result in erroneous analysis, incorrect interpretation, and wrong conclusions which may eventually compromise the right of a fair trial. Hence, a digital forensics investigator has to deal with the complex decision problem from the very start of the investigative process called preparatory phase. The problem could be addressed and possibly solved by using multi criteria decision analysis. The performance of the tool for extracting a specific type of digital evidence, and the relevance of that type of digital evidence to the investigative problem are the two central factors for selecting the best available tool, which we advocate in our work. In this paper we explain the method used and showcase a case study by evaluating two tools using two mobile devices to demonstrate the utility of our proposed approach. The results indicated that XRY (Alt1) dominates UFED (Alt2) for most of the cases after balancing the requirements for both performance and relevance.

0 Replies to “Case Study Based On Decision Theory And Methodology”

Lascia un Commento

L'indirizzo email non verrà pubblicato. I campi obbligatori sono contrassegnati *