Privacy concerns have elevated the popularity of vault apps, especially those available in alternative gray market app stores. Designed to conceal media, vault apps often mimic familiar tools such as calculators, serving as decoys. However, while vault apps enhance user privacy, they present significant challenges to digital forensic practitioners. In particular, it is difficult to access encrypted and deleted data in sensitive and contraband documents encountered in digital forensic investigations. This chapter describes research on Aptoide, a significant gray market app store, that builds on previous work on mainstream stores such as the Google Play Store and Apple’s iOS App Store. A methodology for gray market vault app identification, extraction and forensic analysis is described. The methodology leverages feature extraction from app descriptions along with machine learning algorithms. The research provides insights into the prevalence of vault apps in gray market app stores and sets the stage for in-depth studies of vault apps downloaded from Android app marketplaces.

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Identifying and Analyzing Vault Apps

  • Seth Barrett,
  • Alex Salontai,
  • Rajon Bardhan,
  • Gokila Dorai,
  • Esra Akbas,
  • Patrick Woodell

摘要

Privacy concerns have elevated the popularity of vault apps, especially those available in alternative gray market app stores. Designed to conceal media, vault apps often mimic familiar tools such as calculators, serving as decoys. However, while vault apps enhance user privacy, they present significant challenges to digital forensic practitioners. In particular, it is difficult to access encrypted and deleted data in sensitive and contraband documents encountered in digital forensic investigations. This chapter describes research on Aptoide, a significant gray market app store, that builds on previous work on mainstream stores such as the Google Play Store and Apple’s iOS App Store. A methodology for gray market vault app identification, extraction and forensic analysis is described. The methodology leverages feature extraction from app descriptions along with machine learning algorithms. The research provides insights into the prevalence of vault apps in gray market app stores and sets the stage for in-depth studies of vault apps downloaded from Android app marketplaces.