CFaaS: bilaterally agreed evidence collection
Open accessAbstract
A common cloud forensic model proposed by researchers is ‘Cloud-Forensic-as-a-Service’ where consumers have to access it as a service to collect forensic data from cloud environments. The ‘Cloud-Forensic-as-a-Service’ model raises the question of how it collects digital evidence pertaining to an incident which occurred in the cloud. Currently, types of ‘Cloud-Forensic-as-a-Service’ systems in the literature show that the system is controlled and implemented by the cloud provider, where they unilaterally define the type of evidence that can be collected by the system. A serious limitation of this approach is that it does not offer the consumer sufficient means of performing reasonableness checks to verify that the provider is not accidentally or maliciously contaminating the evidence. To address the problem, the paper proposes a conceptual bilateral Cloud-Forensic-as-a-Service model where both consumers and providers can independently collect, verify the equity of the forensic analysis process and try to resolve potential disputes emerging from the independently collected results. The authors have developed a cloud forensic process model to lead common and significant aspects of a bilateral Cloud-Forensics-as-a-Service model. The paper explicitly discusses the concept of a bilateral Cloud-Forensic-as-a-Service model.
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The authors in [37] established a simultaneous optimisation of server power usage, network connectivity, and migration expense in VM placement.
“Furthermore, the authors in [37] established a simultaneous optimisation of server power usage, network connectivity, and migration expense with workload and host heterogeneity constrained by resource and bandwidth restrictions in VM placement.”
From Energy efficiency in cloud computing data centers: a survey on software technologies (2023) · cites this paper as [37]
The 'Cloud-based technical and conceptual solutions' section discusses collecting forensic evidence from virtual machines, not optimising VM placement. Searches for simultaneous optimisation and for workload, host heterogeneity, resource, and bandwidth constraints found no passage addressing the attributed claim. Page numbers were unavailable in our copy. (LLM, conf=0.76)
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Cited by
Sorted by citations
Energy efficiency in cloud computing data centers: a survey on software technologies
Katal, A., Dahiya, S., & Choudhury, T. (2023) · Cluster Computing · doi:10.1007/s10586-022-03713-0 · Cited by 516 · see citing works
- Authors
- Moussa, A. N., Ithnin, N., & Zainal, A.
- Affiliations
- University of Technology Malaysia (MY)
- Corresponding author
- Moussa, Ahmed Nour
- Venue
- Journal of Cloud Computing
- Published
- 2018-01-05
- Volume
- 7
- Issue
- 1
- ISSN
- 2192-113X (ISSN-L)
- OpenAlex
- W2781653144
- Cited by
- 50
- References
- 71
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 6 · 2023: 3 · 2022: 8 · 2021: 11 · 2020: 10 · 2019: 5 · 2018: 1
- FWCI
- 10.89
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Journal of Cloud Computing Advances Systems and Applications (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Greater South Information System
- Topics
- Physical Sciences › Computer Science › Information Systems › Digital and Cyber Forensics
- Physical Sciences › Computer Science › Information Systems › Cloud Data Security Solutions
- Social Sciences › Political Science and International Relations › Education, Law, and Society
- Keywords
- cloud forensics, digital evidence collection, dispute resolution
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