Y-Y Teing
Greening cloud-enabled big data storage forensics : Syncany as a case study
Teing, Y-Y; Dehghantanha, A; Raymond Choo, K-K; Abdullah, MT; Muda, Z
Authors
A Dehghantanha
K-K Raymond Choo
MT Abdullah
Z Muda
Abstract
The pervasive nature of cloud-enabled big data storage solutions introduces new challenges in the identification, collection, analysis, preservation and archiving of digital evidences. Investigation of such complex platforms to locate and recover traces of criminal activities is a time-consuming process. Hence, cyber forensics researchers are moving towards streamlining the investigation process by locating and documenting residual artefacts (evidences) of forensic value of users’ activities on cloud-enabled big data platforms in order to reduce the investigation time and resources involved in a real-world investigation. In this paper, we seek to determine the data remnants of forensic value from Syncany private cloud storage service, a popular storage engine for big data platforms. We demonstrate the types and the locations of the artefacts that can be forensically recovered. Findings from this research contribute to an in-depth understanding of cloud-enabled big data storage forensics, which can result in reduced time and resources spent in real-world investigations involving Syncany-based cloud platforms.
Citation
Teing, Y., Dehghantanha, A., Raymond Choo, K., Abdullah, M., & Muda, Z. (2019). Greening cloud-enabled big data storage forensics : Syncany as a case study. IEEE Transactions on Sustainable Computing, 4(2), 204-216. https://doi.org/10.1109/TSUSC.2017.2687103
Journal Article Type | Article |
---|---|
Acceptance Date | Mar 14, 2017 |
Online Publication Date | Mar 24, 2017 |
Publication Date | Jun 5, 2019 |
Deposit Date | Aug 2, 2017 |
Publicly Available Date | Feb 15, 2018 |
Journal | IEEE Transactions on Sustainable Computing |
Publisher | Institute of Electrical and Electronics Engineers |
Volume | 4 |
Issue | 2 |
Pages | 204-216 |
DOI | https://doi.org/10.1109/TSUSC.2017.2687103 |
Publisher URL | http://dx.doi.org/10.1109/TSUSC.2017.2687103 |
Related Public URLs | http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=7274860 |
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