Zhang, Bonan, Li, Lin, Chen, Chao, Lee, Ickjai, Lee, Kyungmi, Zhu, Tianqing, and Ong, Kok-Leong (2026) Cross Signal Attacks Against Cardiovascular Authentication Systems. IEEE Transactions on Biometrics, Behavior, and Identity Science. (In Press)

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Abstract

ECG and PPG biometrics are emerging as robust alternatives to traditional authentication methods, particularly in scenarios requiring enhanced security, continuous authentication, and strong resilience against spoofing attacks. This paper investigates and validates the feasibility of launching adversarial attacks against cardiovascular biometric authentication systems by using diffusion models to generate ECG and PPG data that are difficult for authentication algorithms to distinguish from genuine signals. First, we developed a method using a diffusion model to synthesize fake biometric signals for user impersonation, achieving a high attack success rate against completely black-box authentication models. Secondly, we directly extracted users’ rPPG signals from videos and assessed the potential for exploiting video data to compromise users’ ECG-based authentication systems. Our experimental results show that across all algorithms, we achieved an average of 45% attack success rate within five attempts, thus validating the real threat posed by synthetic signals. This finding highlights that even without direct access to the cardiovascular signals used for authentication, an attacker can still launch highly successful attacks by synthesizing signals to deceive the verification system. Our experiments highlight potential vulnerabilities in current biometric systems and underscore the need to develop more secure and attack-resistant authentication technologies.

Item ID:	93776
Item Type:	Article (Refereed Research - C1)
ISSN:	2637-6407
Copyright Information:	© 2026 IEEE. All rights reserved, including rights for text and data mining and training of artificial intelligence and similar technologies. Personal use is permitted.
Date Deposited:	26 Aug 2026 01:00
FoR Codes:	46 INFORMATION AND COMPUTING SCIENCES > 4604 Cybersecurity and privacy > 460407 System and network security @ 100%
SEO Codes:	22 INFORMATION AND COMMUNICATION SERVICES > 2204 Information systems, technologies and services > 220405 Cybersecurity @ 100%
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