abstract: The digital forensics community has neglected email forensics as a process, despite the fact that email remains an important tool in the commission of crime. Current forensic practices focus mostly on that of disk forensics, while email forensics is left as an analysis task stemming from that practice. As there is no well-defined process to be used for email forensics the comprehensiveness, extensibility of tools, uniformity of evidence, usefulness in collaborative/distributed environments, and consistency of investigations are hindered. At present, there exists little support for discovering, acquiring, and representing web-based email, despite its widespread use. To remedy this, a systematic process which includes discovering, acquiring, and representing web-based email for email forensics which is integrated into the normal forensic analysis workflow, and which accommodates the distinct characteristics of email evidence will be presented. This process focuses on detecting the presence of non-obvious artifacts related to email accounts, retrieving the data from the service provider, and representing email in a well-structured format based on existing standards. As a result, developers and organizations can collaboratively create and use analysis tools that can analyze email evidence from any source in the same fashion and the examiner can access additional data relevant to their forensic cases. Following, an extensible framework implementing this novel process-driven approach has been implemented in an attempt to address the problems of comprehensiveness, extensibility, uniformity, collaboration/distribution, and consistency within forensic investigations involving email evidence. / Dissertation/Thesis / M.S. Computer Science 2013

The field of digital forensics is concerned with finding and presenting evidence sourced from digital devices, such as computers and mobile phones. The complexity of such digital evidence is constantly increasing, as is the volume of data which might contain evidence. Current approaches to interpreting and assuring digital evidence rely implicitly on the use of tools and representations made by experts in addressing the concerns of juries and courts. Current forensics tools are best characterised as not easily verifiable, lacking in ease of interoperability, and burdensome on human process. The tool-centric focus of current digital forensics practise impedes access to and transparency of the information represented within digital evidence as much as it assists, by nature of the tight binding between a particular tool and the information that it conveys. We hypothesise that a general and formal representational approach will benefit digital forensics by enabling higher degrees of machine interpretation, facilitating improvements in tool interoperability and validation. Additionally, such an approach will increase human readability. This dissertation summarises research which examines at a fundamental level the nature of digital evidence and digital investigation, in order that improved techniques which address investigation efficiency and assurance of evidence might be identified. The work follows three themes related to this: representation, analysis techniques, and information assurance. The first set of results describes the application of a general purpose representational formalism towards representing diverse information implicit in event based evidence, as well as domain knowledge, and investigator hypotheses. This representational approach is used as the foundation of a novel analysis technique which uses a knowledge based approach to correlate related events into higher level events, which correspond to situations of forensic interest. The second set of results explores how digital forensic acquisition tools scale and interoperate, while assuring evidence quality. An improved architecture is proposed for storing digital evidence, analysis results and investigation documentation in a manner that supports arbitrary composition into a larger corpus of evidence. The final set of results focus on assuring the reliability of evidence. In particular, these results focus on assuring that timestamps, which are pervasive in digital evidence, can be reliably interpreted to a real world time. Empirical results are presented which demonstrate how simple assumptions cannot be made about computer clock behaviour. A novel analysis technique for inferring the temporal behaviour of a computer clock is proposed and evaluated.