메타버스 보안 강화를 위한 동작 기반 사용자 인증
Motion-Based User Authentication for Enhanced Metaverse Security
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참고문헌
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초록
본 논문에서는 메타버스 환경 내에서의 사용자 지속 인증 문제에 대해 다룬다. 최근 메타버스는 개인의 상호작용, 엔터테인먼트, 교육 및 비즈니스 분야에서 중요한 역할을 하고 있으며, 특히 사용자 신원 확인과 관련된 취약점이 주요한 문제로 인식되고 있다. 본 연구는 자세 추정 모델로 메타버스 환경의 캐릭터 움직임을 추출하고 분석하여 사용자의 신원을 확인하는 새로운 방법을 제안한다. 이 방법은 영상 데이터만을 이용하여 사용자를 인증하기 때문에 제한적인 환경에서도 활용할 수 있으며, 다양한 실험을 통해 캐릭터의 움직임이 사용자 식별에 어떻게 기여할 수 있는지를 분석한다. 또한, 이 접근 방식의 다른 디지털 플랫폼으로의 확장 가능성을 탐구한다. 이러한 연구는 메타버스 환경 내에서의 보안 강화와 사용자 신원 확인 방식의 혁신에 중요한 기여할 것으로 기대된다.
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.
참고문헌 (22)
- Ning, Huansheng, "A Survey on the Metaverse: The State-of-the-Art, Technologies, Applications, and Challenges", IEEE Internet of Things Journal, 10(16), pp.14671~14688 (2023)
- Huang, "Security and privacy in metaverse: A comprehensive survey", Big Data Mining and Analytics, 6(2), pp.234~247 (2023)
- Bandi, Ajay, "The power of generative ai: A review of requirements, models, input–output formats, evaluation metrics, and challenges", Future Internet, 15(8), pp.260~ (2023)
- Shoaib, Mohamed R, "Deepfakes, misinformation, and disinformation in the era of frontier ai, generative ai, and large ai models", International Conference on Computer and Applications (2023)
- Ryu, Riseul, "A comprehensive survey of context-aware continuous implicit authentication in online learning environments", IEEE Access, 11, pp.24561~24573 (2023)
- Rodriguez, "PACE: Providing Authentication through Computational Gait Evaluation with Deep learning", Proceedings of the Twenty-fourth International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing, pp.442~446 (2023)
- Odya, Piotr, "User authentication by eye movement features employing SVM and XGBoost classifiers", IEEE Access, 11, pp.93341~93353 (2023)
- Kang, Giluk, "Security and Privacy Requirements for the Metaverse : A Metaverse Applications Perspective", IEEE Communications Magazine, 62(1), pp.148~154 (2023)
- X. Chen, "Privacy Issues and Solutions in Social Network Sites", IEEE Technology and Society Magazine, 31(4), pp.43~53 (2012)
- "The metaverse has a groping problem already" (2021)[URL]
- Gattulli, V., "Touch events and human activities for continuous authentication via smartphone", Scientific Reports, 13(1), pp.10515~ (2023)
- Álvarez-Aparicio, "Biometric recognition through gait analysis", Sci Reports, 12(1), pp.14530~ (2022)
- Wei, Shih-En, "Convolutional pose machines", Proceedings of the IEEE conference on Computer Vision and Pattern Recognition (2016)
- Wang, Jingdong, "Deep high-resolution representation learning for visual recognition", IEEE transactions on pattern analysis and machine intelligence, 43(10), pp.3349~3364 (2020)
- Cao, Zhe, "Realtime multi-person 2d pose estimation using part affinity fields", Proceedings of the IEEE conference on computer vision and pattern recognition (2017)
- Vaswani, Ashish, "Attention is all you need", Advances in neural information processing systems, 30 (2017)
- Bahdanau, Dzmitry, "Neural machine translation by jointly learning to align and translate", 3rd International Conference on Learning Representations (2015)
- Devlin, Jacob, "BERT:Pre-training of Deep Bidirectional Transformers for Language Understanding", Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 1, pp.4171~4186 (2019)
- "Beat Saber" (2024)[URL]
- Nair, Vivek, "Unique identification of 50,000+ virtual reality users from head & hand motion data", 32nd USENIX Security Symposium (USENIX Security 23) (2023)
- Leyfer K, Spivak, "A Continuous user authentication by the classification method based on the dynamic touchscreen biometrics", Proc of the 24th conf of open innov Assoc (FRUCT) (2019), IEEE
- Lee H, "Understanding keystroke dynamics for smartphone users authentication and keystroke dynamics on smartphones built-in motion sensors", Security and Communication Networks (2018)