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This study reviews digital forensics (DF) ontologies to standardize terminology and concepts. It identifies methodologies, types, and applications of 29 ontologies, offering recommendations for future research and practice.

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Area of Science:

  • Computer Science
  • Information Security

Background:

  • Digital media evolution has increased digital crimes, necessitating advancements in computer forensics to digital forensics (DF).
  • Formalizing terminologies and concepts is crucial for common vocabulary comprehension in DF.
  • Ontologies are key initiatives for identifying core concepts and supporting DF.

Purpose of the Study:

  • To systematically review and analyze existing ontologies developed for digital forensics (DF).
  • To identify ontology building methodologies, types, feasibility, evaluation methods, and supported DF phases/subareas.
  • To provide recommendations for future ontology-based support in DF investigations.

Main Methods:

  • Conducted a systematic literature review (SLR) of primary studies on DF ontologies.
  • Analyzed 29 identified ontologies to answer six research questions.
  • Synthesized findings on ontology characteristics and their application in DF.

Main Results:

  • Identified various ontology building methodologies and types used in DF.
  • Determined feasibility points and evaluation/assessment methods for DF ontologies.
  • Cataloged the DF phases and subareas supported by the reviewed ontologies.

Conclusions:

  • The review highlights the diverse landscape of DF ontologies and their current support capabilities.
  • Recommendations are provided to address research gaps and enhance ontology-based support for DF investigations.
  • This work guides researchers and practitioners in leveraging ontologies for more effective digital forensic analysis.