Real-time digital forensic triaging for cloud data analysis using MapReduce on Hadoop framework

Povar, Digambar; Saibharath,; Geethakumari, G.

doi:10.1504/ijesdf.2015.069602

Cited by 1 publication

(2 citation statements)

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“…Since both the data and the tools were on the cloud, this system reduced the storage issues as well the performance issues which existed in standalone workstations (Baar et al, 2014;Beek et al, 2015). Povar et al (2015), introduced a process for triage forensics on clouds using the Hadoop framework. This framework used the MapReduce model in Hadoop for real-time analysis of an HDD using multiple computing nodes.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

“…This framework used the MapReduce model in Hadoop for real-time analysis of an HDD using multiple computing nodes. In this experiment, they used up to 8 nodes and concluded that the overall time could be reduced with an increased number of nodes (Povar et al, 2015). Quick and Choo (2018) introduced a data reduction and data mining framework to handle the issue of ever-increasing data loads.…”

Section: Conclusion and Further Workmentioning

confidence: 99%

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A survey on issues in cloud forensics with an experiment on time consumption

Hettige¹,

Fernando²

2022

Int. j. adv. appl. sci.

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Forensic investigations on cloud platforms are an oft-discussed topic in current digital forensics. Significant growth in cloud platforms is expected in the coming decade. With such growth, cloud forensic investigations may require substantial changes in their approach. The paper surveys the most mentioned issues in cloud forensic literature. It is followed by a description of some of our current work aimed at solving those issues. The first issue that we tried to analyze was the issue of the trustworthiness of the evidence. We identified that the trustworthiness of the Cloud Service Providers is hardly discussed in the literature. Based on previous publications on similar issues on standalone computers, we provided an algorithm as an initial answer to the issue. The algorithm checks for the integrity of the evidence which will be affected in a tampering attempt. The next issue that we considered was time-taken for analysis (time complexity of forensic tools). While the issue has been indicated many times in the literature, we did not find many detailed experiments conducted with tools to observe the processing time over data source size. Therefore, the paper includes the results of an experiment that was performed using an Autopsy forensic tool to measure the time complexity of its operation with a number of source files with increasing sizes. Results indicated that the analyzing times usually increased with the size of the source file and that it might become unmanageable with increasing sizes.

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Section: Conclusion and Further Workmentioning

confidence: 99%

Section: Conclusion and Further Workmentioning

confidence: 99%