Date of Award

3-24-2016

Document Type

Thesis

Degree Name

Master of Science

Department

Department of Electrical and Computer Engineering

First Advisor

Gilbert L. Peterson, PhD.

Abstract

Examiners in the field of digital forensics regularly encounter enormous amounts of data and must identify the few artifacts of evidentiary value. The most pressing 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 primarily 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 little interest from view, allowing examiners to identify artifacts more quickly and accurately. Results from two pilot studies demonstrates that the visualization tool can assist examiners to more accurately and quickly identify artifacts of interest.

AFIT Designator

AFIT-ENG-MS-16-M-029

DTIC Accession Number

AD1053832

Download

Share

COinS