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Automation for digital forensics: Towards a definition for the community.

Gaëtan Michelet¹, Frank Breitinger¹, Graeme Horsman²

¹School of Criminal Justice, University of Lausanne, 1015 Lausanne, Switzerland.

Forensic Science International

|July 6, 2023

Summary

Establishing a common understanding of automation in digital forensics is vital. This study proposes a definition and classification for automation, moving beyond the "wild west" of varied interpretations to advance the discipline.

Keywords:

Automation Definition Digital Forensic investigation Investigative task Practitioner interviews

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Area of Science:

Digital Forensics
Computer Science

Background:

The increasing volume of digital evidence necessitates automation in digital forensics.
A lack of foundational definitions, classification, and terminology creates a fragmented landscape for automation in this field.
Current interpretations of digital forensics automation vary widely, from simple keyword searches to complex autonomous systems.

Purpose of the Study:

To address the absence of a clear foundation for automation in digital forensics.
To propose a standardized definition and classification for automation within the discipline.
To foster a common understanding to promote the advancement of digital forensics automation.

Main Methods:

A comprehensive review of automation literature from digital forensics and related domains.
Conducting interviews with three digital forensics practitioners.
Engaging in discussions with academic domain experts.

Main Results:

A proposed definition for automation in the context of digital forensics.
A classification framework distinguishing between no/basic automation and full (autonomous) automation.
Identification of key considerations for implementing automation in digital forensics.

Conclusions:

Foundational discussions on definition, classification, and terminology are essential for digital forensics automation.
A shared understanding is critical for the promotion and progression of the digital forensics discipline.
Standardizing automation concepts will enable more effective management of digital evidence.