박성규, 류권상,

Vol. 34, No. 3, pp. 493-503, 6월. 2024
10.13089/JKIISC.2024.34.3.493, Full Text:
Keywords: Metaverse, Continuous Authentication, Deep Learning
Abstract

This paper addresses the issue of continuous user authentication within the metaverse environment. Recently, the metaverse plays a vital role in personal interaction, entertainment, education, and business, bringing forth significant security concerns. Particularly, vulnerabilities related to user identity verification have emerged as a major issue. This research proposes a novel method to verify identities by analyzing users' character movements in the metaverse through a pose estimation model. This method uses only video data for authentication, allowing flexibility in limited environments, and investigates how character movements contribute to user identification through various experiments. Furthermore, it explores the potential for extending this approach to other digital platforms. This research is expected to significantly contribute to enhancing security and innovating user identity verification methods in the metaverse environment.

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