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Greening cloud-enabled big data storage forensics: syncany as a case study


Teing, Yee-Yang and Dehghantanha, Ali and Choo, Kim-Kwang Raymond and Muda, Zaiton and Abdullah, Mohd Taufik (2019) Greening cloud-enabled big data storage forensics: syncany as a case study. IEEE Transactions on Sustainable Computing, 4 (2). pp. 204-216. ISSN 2377-3782


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 artifacts 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.

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Official URL or Download Paper: https://ieeexplore.ieee.org/document/7886367

Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.1109/TSUSC.2017.2687103
Publisher: Institute of Electrical and Electronics Engineers
Keywords: Green forensics; Big data forensics; Cloud forensics; Syncany forensics
Depositing User: Nurul Ainie Mokhtar
Date Deposited: 31 May 2023 04:01
Last Modified: 31 May 2023 04:01
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/TSUSC.2017.2687103
URI: http://psasir.upm.edu.my/id/eprint/80012
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