Back to Search
Start Over
Database Forensic Investigation Process Models: A Review
- Source :
- IEEE Access, Vol 8, Pp 48477-48490 (2020)
- Publication Year :
- 2020
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2020.
-
Abstract
- Database Forensic Investigation (DBFI) involves the identification, collection, preservation, reconstruction, analysis, and reporting of database incidents. However, it is a heterogeneous, complex, and ambiguous field due to the variety and multidimensional nature of database systems. A small number of DBFI process models have been proposed to solve specific database scenarios using different investigation processes, concepts, activities, and tasks as surveyed in this paper. Specifically, we reviewed 40 proposed DBFI process models for RDBMS in the literature to offer up-to-date and comprehensive background knowledge on existing DBFI process model research, their associated challenges, issues for newcomers, and potential solutions for addressing such issues. This paper highlights three common limitations of the DBFI domain, which are: 1) redundant and irrelevant investigation processes; 2) redundant and irrelevant investigation concepts and terminologies; and 3) a lack of unified models to manage, share, and reuse DBFI knowledge. Also, this paper suggests three solutions for the discovered limitations, which are: 1) propose generic DBFI process/model for the DBFI field; 2) develop a semantic metamodeling language to structure, manage, organize, share, and reuse DBFI knowledge; and 3) develop a repository to store and retrieve DBFI field knowledge.
- Subjects :
- Structure (mathematical logic)
Process modeling
General Computer Science
Database
Computer science
Process (engineering)
investigation process model
Digital forensics
General Engineering
020207 software engineering
02 engineering and technology
Database forensic
computer.software_genre
Field (computer science)
Metamodeling
Data modeling
Identification (information)
Relational database management system
0202 electrical engineering, electronic engineering, information engineering
020201 artificial intelligence & image processing
General Materials Science
lcsh:Electrical engineering. Electronics. Nuclear engineering
digital forensic
lcsh:TK1-9971
computer
Subjects
Details
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....2eb1ac445edcb81df15ad7504d8543c9
- Full Text :
- https://doi.org/10.1109/access.2020.2976885