Over the decades, computer forensics has expanded from primarily examining computer evidence found on hard drives into the examination of digital devices with increasing storage capacity, to the identification of crimes and illegal activities involving the use of computers, to addressing standards and practices deficiencies, and to addressing the need to educate and train law enforcement, computer forensic technicians, and investigators. This dissertation presents the concept mapping case domain modeling approach to aid examiners/investigators in searching and identifying digital evidence and analyzing the case domain during the examination and analysis phase of the computer forensic investigation. The examination and analysis phases of a computer forensic process are two of the most important phases of the investigative process because the search for and identification of evidence data is crucial to a case; any data uncovered will help determine the guilt or innocence of a suspect. In addition, these phases can become very time consuming and cumbersome. Therefore, finding a method to reduce the amount of time spent searching and identifying potential evidence and analyzing the case domain would greatly enhance the efficiency of the computer forensic process. The hypothesis of this dissertation is that the concept mapping case domain modeling approach can serve as a method for organizing, examining, and analyzing digital forensic evidence and can enhance the quality of forensic examinations without increasing the time required to examine and analyze forensic evidence by more than 5%. Four experiments were conducted to evaluate the effectiveness of the concept mapping case domain modeling approach. Analysis of the experiments supports the hypothesis that the concept mapping case domain modeling approach can be used to organize, search, identify, and analyze digital evidence in an examination.
Identifer | oai:union.ndltd.org:MSSTATE/oai:scholarsjunction.msstate.edu:td-1082 |
Date | 10 December 2010 |
Creators | Tanner, April L |
Publisher | Scholars Junction |
Source Sets | Mississippi State University |
Detected Language | English |
Type | text |
Format | application/pdf |
Source | Theses and Dissertations |
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