Date of Award

Spring 1-1-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

First Advisor

Joe McManus

Second Advisor

Levi Perigo

Third Advisor

Jose Santos

Abstract

With a high variety of Internet of Things (IoT) devices and their inherently high vulnerability level, it is crucial to save investigators’ time for forensic analysis (Bertino3). This research aims to develop an application that would assist with performing forensic analysis on Raspberry Pi devices and would provide user-friendly information to investigators or researchers. Automating many tasks and highlighting areas that need human inspection would optimize investigators’ time and effort (Kebande12). Providing user-friendly graphs and text outputs suitable for reports and communication would empower non-technical persons to understand the results of inspections (Tassone25).

Research methods for this effort include setting up Raspberry Pi devices, performing attacks over the network on one device, collecting commands that get events history, automating these commands as feasible, and visualizing the forensic data. As a result, I identified the tasks that lend themselves to automation, forensic data that can be communicated with visual representations, and I developed an application that assists in performing forensics quickly.

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