research-article

Video is All You Need: Attacking PPG-based Biometric Authentication

Authors:

Yang XiangAuthors Info & Claims

AISec'22: Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security

Pages 57 - 66

https://doi.org/10.1145/3560830.3563722

Published: 07 November 2022 Publication History

Abstract

Unobservable physiological signals enhance biometric authentication systems. Photoplethysmography (PPG) signals are convenient owing to its ease of measurement and are usually well protected against remote adversaries in authentication. Any leaked PPG signals help adversaries compromise the biometric authentication systems, and the advent of remote PPG (rPPG) enables adversaries to acquire PPG signals through restoration. While potentially dangerous, rPPG-based attacks are overlooked because existing methods require the victim's PPG signals. This paper proposes a novel spoofing attack approach that uses the waveforms of rPPG signals extracted from video clips to fool the PPG-based biometric authentication. We develop a new PPG restoration model to accomplish adversarial attacks without leaked PPG signals. Empirical study results on state-of-art PPG-based biometric authentication show that the signals recovered through rPPG pose a severe threat to PPG-based biometric authentication.

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Published In

cover image ACM Conferences

AISec'22: Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security

November 2022

168 pages

ISBN:9781450398800

DOI:10.1145/3560830

Program Chairs:
Ambra Demontis
University of Cagliari, Italy
,
Xinyun Chen
Google Brain, USA
,
Florian Tramèr
ETH Zürich, Switzerland

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Published: 07 November 2022

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Cited By

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https://doi.org/10.1109/TIFS.2024.3468624
Yao APal SDong CLi XLiu X(2024)A Framework for User Biometric Privacy Protection in UAV Delivery Systems with Edge Computing2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops)10.1109/PerComWorkshops59983.2024.10502849(631-636)Online publication date: 11-Mar-2024
https://doi.org/10.1109/PerComWorkshops59983.2024.10502849
Zhang WZhou XChen H(2024)PressHeart: A Two-Factor Authentication Mechanism via PPG Signals for Wearable DevicesICC 2024 - IEEE International Conference on Communications10.1109/ICC51166.2024.10622232(4662-4667)Online publication date: 9-Jun-2024
https://doi.org/10.1109/ICC51166.2024.10622232
Hinatsu SWada S(2024)Biometric Authentication Using Chest Wall Displacement Recorded by VHF-Band Loop AntennaIEEE Access10.1109/ACCESS.2024.352101312(196475-196487)Online publication date: 2024
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Wang JShan CLiu LHou Z(2024)Camera-based physiological measurementNeurocomputing10.1016/j.neucom.2024.127282575:COnline publication date: 16-May-2024
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Yao ZLi LZhang LGuo FChen CZhang J(2024)Deceptive Waves: Embedding Malicious Backdoors in PPG AuthenticationWeb Information Systems Engineering – WISE 202410.1007/978-981-96-0567-5_19(258-272)Online publication date: 3-Dec-2024
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Li LChen CPan LZhang LZhang JXiang Y(2023)SigA: rPPG-based Authentication for Virtual Reality Head-mounted DisplayProceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3607199.3607209(686-699)Online publication date: 16-Oct-2023
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