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The Advanced Data Acquisition Model (ADAM): A process model for digital forensic practice

Adams, Richard (2012) The Advanced Data Acquisition Model (ADAM): A process model for digital forensic practice. PhD thesis, Murdoch University.

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Given the pervasive nature of information technology, the nature of evidence presented in court is now less likely to be paper-based and in most instances will be in electronic form . However, evidence relating to computer crime is significantly different from that associated with the more ‘traditional’ crimes for which, in contrast to digital forensics, there are well-established standards, procedures and models to which law courts can refer.

The key problem is that, unlike some other areas of forensic practice, digital forensic practitioners work in a number of different environments and existing process models have tended to focus on one particular area, such as law enforcement, and fail to take into account the different needs of those working in other areas such as incident response or ‘commerce’.

This thesis makes an original contribution to knowledge in the field of digital forensics by developing a new process model for digital data acquisition that addresses both the practical needs of practitioners working in different areas of the field and the expectation of law courts for a formal description of the process undertaken to acquire digital evidence.

The methodology adopted for this research is design science on the basis that it is particularly suited to the task of creating a new process model and an ‘ideal approach’ in the problem domain of digital forensic evidence. The process model employed is the Design Science Research Process (DSRP) (Peffers, Tuunanen, Gengler, Rossi, Hui, Virtanen and Bragge, 2006) that has been widely utilised within information systems research.

A review of current process models involving the acquisition of digital data is followed by an assessment of each of the models from a theoretical perspective, by drawing on the work of Carrier and Spafford (2003)1, and from a legal perspective by reference to the Daubert test2. The result of the model assessment is that none provide a description of a generic process for the acquisition of digital data, although a few models contain elements that could be considered for adaptation as part of a new model.

Following the identification of key elements for a new model (based on the literature review and model assessment) the outcome of the design stage is a three-stage process model called the Advance Data Acquisition Model (ADAM) that comprises of three UML3 Activity diagrams, overriding Principles and an Operation Guide for each stage. Initial testing of the ADAM (the Demonstration stage from the DSRP) involves a ‘desk check’ using both in-house documentation relating to three digital forensic investigations and four narrative scenarios. The results of this exercise are fed back into the model design stage and alterations made as appropriate.

The main testing of the model (the DSRP Evaluation stage) involves independent verification and validation of the ADAM utilising two groups of ‘knowledgeable people’. The first group, the Expert Panel, consists of international ‘subject matter experts’ from the domain of digital forensics. The second group, the Practitioner Panel, consists of peers from around Australia that are digital forensic practitioners and includes a representative from each of the areas of relevance for this research, namely: law enforcement, commerce and incident response. Feedback from the two panels is considered and modifications applied to the ADAM as appropriate.

This thesis builds on the work of previous researchers and demonstrates how the UML can be practically applied to produce a generic model of one of the fundamental digital forensic processes, paving the way for future work in this area that could include the creation of models for other activities undertaken by digital forensic practitioners. It also includes the most comprehensive review and critique of process models incorporating the acquisition of digital forensics yet undertaken.

Item Type: Thesis (PhD)
Murdoch Affiliation(s): School of Information Technology
Supervisor(s): Hobbs, Val and Mann, Graham
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