Date of Award
Master of Science (MS)
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.
Madinger, Dilara, "User-Friendly Interface for Forensic Analysis Using Raspberry Pi" (2018). Interdisciplinary Telecommunications Graduate Theses & Dissertations. 30.