The Industrial Internet of Things (IIoT) plays a critical role in modern industrial systems, contributing to increased efficiency, productivity, and innovation. However,its rapid evolution and the complexity of devices pose significant challenges to digital forensics readiness (DFR). This thesis aims to provide a set of guidelines forimplementing DFR within IIoT environments, addressing challenges such as datacollection and logging, device and data identification, verification, security, analysis,and reporting. The framework was developed through rigorous research processesand guided by expert interviews and a final survey, adhering to design science principles. Although the study’s outcomes are subject to some limitations, such as a smallnumber of experts for evaluation, the research contributes to a significant gap in theexisting literature by providing a robust, adaptable, and comprehensive guide to DFRin IIoT. Offering a foundation for future research to build upon, enhance DFR, andaddressing emerging IIoT technologies and scenarios.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:lnu-122091 |
| Date | January 2023 |
| Creators | Molinaro, Paolo, Wagner, Raya |
| Publisher | Linnéuniversitetet, Institutionen för datavetenskap och medieteknik (DM) |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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