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A case-based reasoning method for locating evidence during digital forensic device triage
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2014 | Decision Support Systems | Citations: 0
Authors: Horsman, Graeme; Laing, Christopher; Vickers, Paul

Abstract: The role of triage in digital forensics is disputed, with some practitioners que ... Expand

Abstract: The role of triage in digital forensics is disputed, with some practitioners questioning its reliability for identifying evidential data. Although successfully implemented in the field of medicine, triage has not established itself to the same degree in digital forensics. This article presents a novel approach to triage for digital forensics. Case-Based Reasoning Forensic Triager (CBR-FT) is a method for collecting and reusing past digital forensic investigation information in order to highlight likely evidential areas on a suspect operating system, thereby helping an investigator to decide where to search for evidence. The CBR-FT framework is discussed and the results of twenty test triage examinations are presented. CBR-FT has been shown to be a more effective method of triage when compared to a practitioner using a leading commercial application. Collapse

Semantic filters: precision score digital forensics

Topics: knowledge base IT productivity digital forensics technological change criminality

Methods: machine learning

Theories: theory of case-based reasoning
Post-retrieval search hit clustering to improve information retrieval effectiveness: Two digital forensics case studies
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2011 | Decision Support Systems | Citations: 0
Authors: Beebe, Nicole Lang; Clark, Jan Guynes; Dietrich, Glenn B.; Ko, Myung S.; Ko, Daijin

Abstract: This research extends text mining and information retrieval research to the digi ... Expand

Abstract: This research extends text mining and information retrieval research to the digital forensic text string search process. Specifically, we used a self-organizing neural network (a Kohonen Self-Organizing Map) to conceptually cluster search hits retrieved during a real-world digital forensic investigation. We measured information retrieval effectiveness (e.g., precision, recall, and overhead) of the new approach and compared them against the current approach. The empirical results indicate that the clustering process significantly reduces information retrieval overhead of the digital forensic text string search process, which is currently a very burdensome endeavor. Collapse

Semantic filters: precision score digital forensics

Topics: digital forensics usability user interface information retrieval search engine

Methods: cluster analysis machine learning experiment design artifact simulation

Theories: theory of bounded rationality theory of task technology fit

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A case-based reasoning method for locating evidence during digital forensic device triage

Post-retrieval search hit clustering to improve information retrieval effectiveness: Two digital forensics case studies