Study of identifying and managing the potential evidence for effective Android forensics

Dohyun Kim, Sangjin Lee

Research output: Contribution to journalArticlepeer-review

14 Citations (Scopus)

Abstract

Since the advent of various IoT devices, the need for digital forensics for mobile devices that people use most closely in their daily lives has continued to grow. Besides, as Bring Your Own Device (BYOD) becomes the trend, devices store business-related information as well as privacy. Thus, mobile devices are becoming the most critical evidence of digital forensics. For practical mobile forensics, it is necessary to identify crime-related items among the many files inside the device accurately. Also, various user information for user behavior analysis from these files should be effectively extracted and managed as potential evidence to ensure integrity. This paper proposes an efficient forensics investigation method for mobile devices with Android OS, which holds the highest share in the world among mobile devices. In this paper, we studied data pre-processing (classification and identification of data), data analysis, evidence management, and Android data Taxonomy.

Original languageEnglish
Article number200897
JournalForensic Science International: Digital Investigation
Volume33
DOIs
Publication statusPublished - 2020 Jun

Keywords

  • Android forensics
  • Android forensics XML
  • Data classification
  • Data grouping
  • Data taxonomy
  • Evidence management
  • Mobile data analysis
  • Mobile forensics
  • Potential evidence identification

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Pathology and Forensic Medicine
  • Law
  • Medical Laboratory Technology

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