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Domain-Adaptive Power Profiling Analysis Strategy for the Metaverse
  • +4
  • Aidong Chen,
  • Xiang Li,
  • Ning Yang,
  • Weifeng Liu,
  • Yanlong Zhang,
  • Shuo Wang,
  • Jing Zhou
Aidong Chen
Beijing Union University

Corresponding Author:aidongise@gmail.com

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Xiang Li
Beijing Union University
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Ning Yang
Beijing Union University
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Weifeng Liu
Institute of Semiconductors Chinese Academy of Sciences
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Yanlong Zhang
Beijing Microelectronic Technology Institute
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Shuo Wang
Beijing Microelectronic Technology Institute
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Jing Zhou
Beijing Microelectronic Technology Institute
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Abstract

In the surge of the digital era, the Metaverse, as a groundbreaking concept, has become a focal point in the technology sector. It is reshaping human work and life patterns, carving out a new realm of virtual and real interaction. However, the rapid development of the Metaverse brings along novel challenges in security and privacy. In this multifaceted and complex technological environment, data protection is of paramount importance. The innovative capabilities of high-end devices and functions in the Metaverse, owing to advanced integrated circuit technology, face unique threats from Side-Channel Analysis (SCA), potentially leading to breaches in user privacy. Addressing the issue of domain differences caused by different hardware devices, which impact the generalizability of the analysis model and the accuracy of analysis, this paper proposes a strategy of Portability Power Profiling Analysis (PPPA). Combining domain adaptation and deep learning techniques, it models and calibrates the domain differences between the profiling and target devices, enhancing the model’s adaptability in different device environments. Experiments show that our method can recover the correct key with as few as 389 power traces, effectively recovering keys across different devices. This paper underscores the effectiveness of cross-device SCA, focusing on the adaptability and robustness of analysis models in different hardware environments, thereby enhancing the security of user data privacy in the Metaverse environment.
Submitted to International Journal of Network Management
26 Jan 2024Review(s) Completed, Editorial Evaluation Pending
11 Apr 20241st Revision Received
11 Apr 2024Submission Checks Completed
11 Apr 2024Assigned to Editor
30 May 2024Editorial Decision: Accept