Study of identifying and managing the potential evidence for effective Android forensics
- Authors
- Kim, Dohyun; Lee, Sangjin
- Issue Date
- 6월-2020
- Publisher
- ELSEVIER SCI LTD
- Keywords
- Mobile forensics; Android forensics; Data grouping; Potential evidence identification; Data classification; Mobile data analysis; Evidence management; Data taxonomy; Android forensics XML
- Citation
- FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION, v.33
- Indexed
- SCIE
SCOPUS
- Journal Title
- FORENSIC SCIENCE INTERNATIONAL-DIGITAL INVESTIGATION
- Volume
- 33
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/55477
- DOI
- 10.1016/j.fsidi.2019.200897
- ISSN
- 2666-2817
- 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. (C) 2019 Elsevier Ltd. All rights reserved.
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Collections - School of Cyber Security > Department of Information Security > 1. Journal Articles
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