Cloud computing offers users low-cost access to computing resources that are scalable and flexible. However, it is not without its challenges, especially in relation to security. Cloud resources can be leveraged for criminal activities and the architecture of the ecosystem makes digital investigation difficult in terms of evidence identification, acquisition and examination. However, these same resources can be leveraged for the purposes of digital forensics, providing facilities for evidence acquisition, analysis and storage. Alternatively, existing forensic capabilities can be used in the Cloud as a step towards achieving forensic readiness. Tools can be added to the Cloud which can recover artefacts of evidential value. This research investigates whether artefacts that have been recovered from the Xen Cloud Platform (XCP) using existing tools have evidential value. To determine this, it is broken into three distinct areas: adding existing tools to a Cloud ecosystem, recovering artefacts from that system using those tools and then determining the evidential value of the recovered artefacts. From these experiments, three key steps for adding existing tools to the Cloud were determined: the identification of the specific Cloud technology being used, identification of existing tools and the building of a testbed. Stemming from this, three key components of artefact recovery are identified: the user, the audit log and the Virtual Machine (VM), along with two methodologies for artefact recovery in XCP. In terms of evidential value, this research proposes a set of criteria for the evaluation of digital evidence, stating that it should be authentic, accurate, reliable and complete. In conclusion, this research demonstrates the use of these criteria in the context of digital investigations in the Cloud and how each is met. This research shows that it is possible to recover artefacts of evidential value from XCP.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:716164 |
| Date | January 2017 |
| Creators | Mustafa, Zareefa S. |
| Contributors | Maddison Warren, Annie ; Morris, Sarah ; Nobles, Philip |
| Publisher | Cranfield University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://dspace.lib.cranfield.ac.uk/handle/1826/12017 |
Page generated in 0.0022 seconds