An abstract model for digital forensic analysis tools - A foundation for systematic error mitigation analysis

IF 2 4区 医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Forensic Science International-Digital Investigation Pub Date : 2024-03-01 DOI:10.1016/j.fsidi.2023.301679
Christopher Hargreaves , Alex Nelson , Eoghan Casey
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Abstract

As automation within digital forensic tools becomes more advanced there is a need for a systematic approach to ensure the validity, reliability, and standardization of digital forensic results. This paper argues for intermediate output in a standardized format within digital forensic tools to allow a methodical approach to tool validation that targets errors at each stage of processing. To achieve this, a detailed process model of digital forensic analysis tools is created, extrapolating the details of the internal processes performed by monolithic forensic tools. The research deconstructs the process flow within tools and presents an ‘abstract digital forensic tool’, revisiting earlier abstraction layer ideas. This not only identifies the interconnected processes within tools but allows discussion of the potential error that could be introduced at each stage, and how it could potentially propagate within a tool. A demonstration, with a dataset, is also included, structurally annotated using Cyber-investigation Analysis Standard Expression (CASE).

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数字取证分析工具的抽象模型--系统性错误缓解分析的基础
随着数字取证工具的自动化越来越先进,需要一种系统的方法来确保数字取证结果的有效性、可靠性和标准化。本文认为,数字取证工具应采用标准化格式的中间输出,以便有条不紊地对工具进行验证,在处理的每个阶段找出错误。为实现这一目标,本文创建了数字取证分析工具的详细流程模型,并推断了单片式取证工具执行的内部流程细节。研究解构了工具内部的流程,提出了 "抽象数字取证工具",重温了早期的抽象层理念。这不仅能识别工具内部相互关联的流程,还能讨论每个阶段可能引入的潜在错误,以及错误如何在工具内部传播。此外,还包括一个数据集演示,并使用网络调查分析标准表达式(CASE)进行结构注释。
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来源期刊
CiteScore
5.90
自引率
15.00%
发文量
87
审稿时长
76 days
期刊最新文献
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