A RAM triage methodology for Hadoop HDFS forensics.
- Submitting institution
-
Edinburgh Napier University
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 1110851
- Type
- D - Journal article
- DOI
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10.1016/j.diin.2016.07.003
- Title of journal
- Digital Investigation
- Article number
- -
- First page
- 96
- Volume
- 18
- Issue
- -
- ISSN
- 1742-2876
- Open access status
- Compliant
- Month of publication
- July
- Year of publication
- 2016
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- As one of only two papers accepted for the journal's special edition entitled Cloud forensics: State-of-the-art and future directions, this work "has contributed to filling the knowledge gap between existing scholarship and challenges faced by the cloud forensic community" according to the editors (https://doi.org/10.1016/j.diin.2016.08.003). The method was expanded by Khader et al (2018), who added a detailed analysis of metadata changes. The paper resulted in an invitation to speak at the Scot-Secure Summit 2020 (19/2/2020, https://www.scot-secure.com/), which is the largest annual cybersecurity event in Scotland and attracted 350 participants, mainly from industry and public sector.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -