Article ID Journal Published Year Pages File Type
4955645 Digital Investigation 2017 26 Pages PDF
Abstract
Examiners in the field of digital forensics regularly encounter enormous amounts of data and must identify the few artifacts of evidentiary value. One challenge these examiners face is manual reconstruction of complex datasets with both hierarchical and associative relationships. The complexity of this data requires significant knowledge, training, and experience to correctly and efficiently examine. Current methods provide text-based representations or low-level visualizations, but levee the task of maintaining global context of system state on the examiner. This research presents a visualization tool that improves analysis methods through simultaneous representation of the hierarchical and associative relationships and local detailed data within a single page application. A novel whitelisting feature further improves analysis by eliminating items of less interest from view. Results from a pilot study demonstrate that the visualization tool can assist examiners to more accurately and quickly identify artifacts of interest.
Related Topics
Physical Sciences and Engineering Computer Science Computer Networks and Communications
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