Systematic Literature Review on Wearable Digital Forensics: Acquisition Methods, Analysis Techniques, Tools, and Future Directions

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5 Scopus citations

Abstract

Wearable devices have become increasingly prevalent in workplaces worldwide, offering valuable information and forensic data to dispute false testimonies or track a victim during an incident. However, the use of wearables as sources of digital evidence remains relatively unexplored. Further, there has been no systematic review of data extraction and analysis techniques for wearables. This systematic literature review (SLR) addresses these gaps by: 1) exploring methods used by digital investigators to extract data from wearables; 2) surveying prevalent data analysis techniques for wearable digital forensics; 3) examining digital forensics tools used in wearable investigations; 4) proposing a taxonomy integrating data extraction methods, analysis techniques, and forensic tools; and 5) identifying gaps in current wearable forensics research to guide future studies. The SLR covered articles published in the last decade (2012-2022) on the extraction and analysis of evidence from wearables. Consequently, 50 primary studies relevant to the study's objectives were identified. Five main extraction techniques were identified: 1) manual; 2) logical; 3) physical; 4) network communication; and 5) electromagnetic. Logical data extraction accounted for approximately 48% of these methods, followed by physical extraction (31%). Notably, 47% employed multiple extraction techniques. Trivial, nontrivial, and anti-forensic techniques were the most commonly used by criminals to evade forensic investigations. Moreover, most tools examined for wearable investigations were from nonwearable domains. The review highlighted several research gaps that require future investigation to develop more sustainable approaches to wearable digital forensics. This comprehensive overview highlighted the need for advancing forensic methodologies to address the unique challenges posed by the wearable technology.

Original languageEnglish
Pages (from-to)1320-1342
Number of pages23
JournalIEEE Internet of Things Journal
Volume12
Issue number2
DOIs
StatePublished - 2025

Keywords

  • Acquisition
  • analysis
  • digital evidence
  • digital forensics tools
  • extraction
  • Internet of Things (IoT)
  • wearable digital forensics

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