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Digital forensic investigation framework for the metaverse.

Authors :
Seo, Seunghee
Seok, Byoungjin
Lee, Changhoon
Source :
Journal of Supercomputing. Jun2023, Vol. 79 Issue 9, p9467-9485. 19p.
Publication Year :
2023

Abstract

The Metaverse is currently becoming a massive technology platform and is considered to be the next significant development in global technology and business landscapes. The Metaverse is a digital platform that people can enter or transport virtual items with a device as a medium, implemented as virtual but very similar to the real world through the concept of the digital twin as used in smart cities. The Metaverse is currently in its infancy but is developing gradually. However, the potential threat of crime in this new world already has become a concern. As the Metaverse becomes more similar to the real world, the events that occur in it can affect the real world as well. Therefore, digital forensic research on the Metaverse is necessary to investigate crimes occurring in the Metaverse, such as money laundering, virtual burglaries, virtual theft, and fraud. In this paper, we present the conceptual architecture of the Metaverse and discuss what are termed metacrimes, crimes that may occur within the Metaverse, and address the need for research on digital forensic investigations of the Metaverse. Furthermore, we propose a Metaverse forensic framework for the first time; it consists of four phases based on the digital forensic guidance of NIST. These are data collection, examination and retrieval of evidence, analysis, and reporting. In the framework, we provide three different procedures in the data collection phase and examination phase by dividing them into three categories: user, service, and the Metaverse platform. Finally, we discuss the challenge of digital forensic investigations in the Metaverse from three standpoints: data possession, anti-forensics, and privacy. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09208542
Volume :
79
Issue :
9
Database :
Academic Search Index
Journal :
Journal of Supercomputing
Publication Type :
Academic Journal
Accession number :
163295529
Full Text :
https://doi.org/10.1007/s11227-023-05045-1