
doi: 10.1002/cpe.4277
SummaryThe significant increase in the volume, variety, and velocity of data complicates cloud forensic efforts, and such (big) evidential data will, at some point, become too (computationally) expensive to be fully identified, collected, and analysed in a timely manner. Thus, it is important for digital forensic practitioners to have an up‐to‐date knowledge of relevant data artefacts that could be forensically recovered from the cloud product under investigation. In this paper, CloudMe, a popular cloud storage service, is studied. The types and locations of the artefacts relating to the installation and uninstallation of CloudMe client application, logging in and out, and file synchronization events from the computer desktop and mobile clients are described. Findings from this research will also help inform future development of tools and techniques (e.g., data mining techniques) for cloud‐enabled big data endpoint forensics investigation.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 30 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
