Horsman Graeme, Sunde Nina
School of Health and Life Sciences, Teesside University, Middlesbrough, Tees Valley, UK.
The Norwegian Police University College/University of Oslo, Pb. 2109 Vika, 0125 Oslo, Norway.
Sci Justice. 2022 Mar;62(2):171-180. doi: 10.1016/j.scijus.2022.01.002. Epub 2022 Jan 20.
As digital forensics continues to play an important role in criminal investigations, its investigative work must be underpinned with well-defined and robust methodologies. Over the last 20 years, a substantial body of research has been produced to define and codify the digital forensic investigation process and the stages/sub-processes involved. Whilst current digital forensic investigation process models provide a solid foundation, it is argued that existing attempts often only focus on those physical tasks, which a practitioner must carry out at any given stage of an examination, omitting to identify those core thought processes, decisions and behaviours that form part of effective investigative practices. This work presents the Digital Forensic Workflow Model (DFWM), a novel approach to the structuring and definition of the procedures and tasks involved in the digital forensic investigation process starting from the initial 'Review of Client Requirements & Planning' stage, right through to the 'Evaluation of Deployed Workflow' stage. The DFWM contributes to the digital forensic management toolbox, where it enables the identification and management of risk and supports error mitigation at each stage of the workflow. The paper demonstrates how the DFWM functions as a framework for unboxing the digital forensic investigation process based on the investigative strategy of the particular case, providing a detailed structure and depiction of the physical and investigative tasks and decisions. From a research perspective, DFWM is a descriptive starting point, and future empirical studies may expand and provide further detail to the various physical and cognitive tasks and associated risks during the DF workflow.
随着数字取证在刑事调查中继续发挥重要作用,其调查工作必须以明确且稳健的方法为支撑。在过去20年里,已经开展了大量研究来定义和编纂数字取证调查过程以及其中涉及的阶段/子过程。虽然当前的数字取证调查过程模型提供了坚实的基础,但有人认为,现有的尝试往往只关注从业者在检查的任何给定阶段必须执行的那些物理任务,而忽略了识别那些构成有效调查实践一部分的核心思维过程、决策和行为。本文提出了数字取证工作流模型(DFWM),这是一种全新的方法,用于构建和定义从最初的“客户需求审查与规划”阶段到“已部署工作流评估”阶段的数字取证调查过程中所涉及的程序和任务。DFWM为数字取证管理工具箱做出了贡献,它能够识别和管理风险,并在工作流的每个阶段支持减轻错误。本文展示了DFWM如何作为一个框架,根据特定案件的调查策略来剖析数字取证调查过程,提供物理和调查任务及决策的详细结构和描述。从研究角度来看,DFWM是一个描述性的起点,未来的实证研究可能会扩展并进一步详细阐述DF工作流期间的各种物理和认知任务以及相关风险。