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WavoID: Robust and Secure Multi-modal User Identification via mmWave-voice Mechanism

Published: 29 October 2023 Publication History

Abstract

With the increasing deployment of voice-controlled devices in homes and enterprises, there is an urgent demand for voice identification to prevent unauthorized access to sensitive information and property loss. However, due to the broadcast nature of sound wave, a voice-only system is vulnerable to adverse conditions and malicious attacks. We observe that the cooperation of millimeter waves (mmWave) and voice signals can significantly improve the effectiveness and security of user identification. Based on the properties, we propose a multi-modal user identification system (named WavoID) by fusing the uniqueness of mmWave-sensed vocal vibration and mic-recorded voice of users. To estimate fine-grained waveforms, WavoID splits signals and adaptively combines useful decomposed signals according to correlative contents in both mmWave and voice. An elaborated anti-spoofing module in WavoID comprising biometric bimodal information defend against attacks. WavoID produces and fuses the response maps of mmWave and voice to improve the representation power of fused features, benefiting accurate identification, even facing adverse circumstances. We evaluate WavoID using commercial sensors on extensive experiments. WavoID has significant performance on user identification with over 98% accuracy on 100 user datasets.

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    cover image ACM Conferences
    UIST '23: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology
    October 2023
    1825 pages
    ISBN:9798400701320
    DOI:10.1145/3586183
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    Published: 29 October 2023

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    Author Tags

    1. User authentication
    2. mmWave sensing
    3. multi-modal fusion
    4. voice identification

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    • (2024)VibSpeechProceedings of the 33rd USENIX Conference on Security Symposium10.5555/3698900.3699124(3997-4014)Online publication date: 14-Aug-2024
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    • (2024)Behaviors Speak More: Achieving User Authentication Leveraging Facial Activities via mmWave SensingProceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems10.1145/3666025.3699330(169-183)Online publication date: 4-Nov-2024
    • (2024)A New mmWave-Speech Multimodal Speech System for Voice User InterfaceGetMobile: Mobile Computing and Communications10.1145/3640087.364009627:4(31-35)Online publication date: 8-Jan-2024
    • (2024)PhaDe: Practical Phantom Spoofing Attack Detection for Autonomous VehiclesIEEE Transactions on Information Forensics and Security10.1109/TIFS.2024.337619219(4199-4214)Online publication date: 14-Mar-2024

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