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VibHead: An Authentication Scheme for Smart Headsets through Vibration

Published: 11 May 2024 Publication History

Abstract

Recent years have witnessed the fast penetration of Virtual Reality (VR) and Augmented Reality (AR) systems into our daily life, the security and privacy issues of the VR/AR applications have been attracting considerable attention. Most VR/AR systems adopt head-mounted devices (i.e., smart headsets) to interact with users and the devices usually store the users’ private data. Hence, authentication schemes are desired for the head-mounted devices. Traditional knowledge-based authentication schemes for general personal devices have been proved vulnerable to shoulder-surfing attacks, especially considering the headsets may block the sight of the users. Although the robustness of the knowledge-based authentication can be improved by designing complicated secret codes in virtual space, this approach induces a compromise of usability. Another choice is to leverage the users’ biometrics; however, it either relies on highly advanced equipments which may not always be available in commercial headsets or introduce heavy cognitive load to users.
In this paper, we propose a vibration-based authentication scheme, VibHead, for smart headsets. Since the propagation of vibration signals through human heads presents unique patterns for different individuals, VibHead employs a CNN-based model to classify registered legitimate users based the features extracted from the vibration signals. We also design a two-step authentication scheme where the above user classifiers are utilized to distinguish the legitimate user from illegitimate ones. We implement VibHead on a Microsoft HoloLens equipped with a linear motor and an IMU sensor which are commonly used in off-the-shelf personal smart devices. According to the results of our extensive experiments, with short vibration signals (≤1s), VibHead has an outstanding authentication accuracy; both FAR and FRR are around 5%.

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Published In

cover image ACM Transactions on Sensor Networks
ACM Transactions on Sensor Networks  Volume 20, Issue 4
July 2024
603 pages
EISSN:1550-4867
DOI:10.1145/3618082
  • Editor:
  • Wen Hu
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

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Publication History

Published: 11 May 2024
Online AM: 17 August 2023
Accepted: 25 July 2023
Revised: 29 June 2023
Received: 30 January 2023
Published in TOSN Volume 20, Issue 4

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Author Tags

  1. User authentication
  2. vibration signals
  3. smart headsets

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  • NSFC
  • Shandong Provincial Natural Science Foundation

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View all
  • (2024)Simple but Effective Raw-Data Level Multimodal Fusion for Composed Image RetrievalProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657727(229-239)Online publication date: 10-Jul-2024
  • (2024)ATOM: AI-Powered Sustainable Resource Management for Serverless Edge Computing EnvironmentsIEEE Transactions on Sustainable Computing10.1109/TSUSC.2023.33481579:6(817-829)Online publication date: Nov-2024
  • (2024)Incorporating Part of Speech Information in span representation for Named Entity RecognitionApplied Soft Computing10.1016/j.asoc.2024.111844163:COnline publication date: 1-Sep-2024

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