Dataset construction challenges for digital forensics.

Area of Science:

• Digital Forensics
• Computer Science
• Information Security

Background:

• The digital forensic field requires reliable testing to ensure practitioner process integrity.
• Effective testing necessitates well-constructed and documented test datasets.
• Current lack of standards for dataset creation in digital forensics hinders reliability.

Purpose of the Study:

• To address the need for standardized digital forensic dataset creation.
• To define minimum requirements for creating valuable digital forensic datasets.
• To guide practitioners in generating high-quality test data.

Main Methods:

• Categorization of digital forensic datasets into three types: tool/process evaluation, actions, and scenario-based.
• Outlining minimum creation requirements for each dataset category.
• Discussion of best practices for dataset development.

Main Results:

• Definition of three distinct digital forensic dataset categories.
• Establishment of minimum requirements for the creation of each category.
• Framework provided to enhance dataset value and reliability.

Conclusions:

• Standardized dataset creation is essential for digital forensic reliability.
• Defined categories and requirements will improve test dataset quality.
• This work supports practitioners in creating maximum-value digital forensic datasets.