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A Review of Mobile Forensic Investigation Process Models
Malmö University, Faculty of Technology and Society (TS), Department of Computer Science and Media Technology (DVMT). Malmö University, Internet of Things and People (IOTAP).ORCID iD: 0000-0003-4071-4596
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2020 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 173359-173375Article, review/survey (Refereed) Published
Abstract [en]

Mobile Forensics (MF) field uses prescribed scientific approaches with a focus on recovering Potential Digital Evidence (PDE) from mobile devices leveraging forensic techniques. Consequently, increased proliferation, mobile-based services, and the need for new requirements have led to the development of the MF field, which has in the recent past become an area of importance. In this article, the authors take a step to conduct a review on Mobile Forensics Investigation Process Models (MFIPMs) as a step towards uncovering the MF transitions as well as identifying open and future challenges. Based on the study conducted in this article, a review of the literature revealed that there are a few MFIPMs that are designed for solving certain mobile scenarios, with a variety of concepts, investigation processes, activities, and tasks. A total of 100 MFIPMs were reviewed, to present an inclusive and up-to-date background of MFIPMs. Also, this study proposes a Harmonized Mobile Forensic Investigation Process Model (HMFIPM) for the MF field to unify and structure whole redundant investigation processes of the MF field. The paper also goes the extra mile to discuss the state of the art of mobile forensic tools, open and future challenges from a generic standpoint. The results of this study find direct relevance to forensic practitioners and researchers who could leverage the comprehensiveness of the developed processes for investigation.

Place, publisher, year, edition, pages
IEEE, 2020. Vol. 8, p. 173359-173375
Keywords [en]
Smart phones, Analytical models, Unified modeling language, Tools, Digital forensics, Mobile forensics, investigation process model
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mau:diva-36642DOI: 10.1109/ACCESS.2020.3014615ISI: 000575905200001OAI: oai:DiVA.org:mau-36642DiVA, id: diva2:1498990
Available from: 2020-11-06 Created: 2020-11-06 Last updated: 2022-11-02Bibliographically approved

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Kebande, Victor R.

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