Bio-CEC: A Secure and Efficient Cloud-Edge Collaborative Biometrics System using Cancelable Biometrics

Xuefei Chen, Xiao Liu, Frank Jiang, Aiting Yao, Jia Xu, Hui Zhang, Xiang Wu, Xuejun Li

Abstract: Biometric technology has driven the rise of Biometrics as a Service (BaaS) due to its unique security and convenience. However, in the traditional cloud-based BaaS systems, raw biometric data leakage and biometric efficiency issues are still concerns, which may reduce user trust and engagement in biometric services. In this paper, we propose an innovative BaaS system named Bio-CEC in a Cloud-Edge Cooperative environment. Bio-CEC features a novel biometric template transformation scheme, rooted in multivariate polynomial transformation and random virtual feature replacement. This innovative scheme enables the revocation and regeneration of biometric templates, enhancing security in case of system breaches. For the biometric template protect scheme, a template matching algorithm using filtering operations is proposed, aiming to facilitate secure and accurate authentication within the transformation domain. Our comprehensive experiments and in-depth safety analysis verify the superiority of Bio-CEC. The results clearly demonstrate that Bio-CEC outperforms traditional cloud-based biometric system and provides a safer and more efficient solution for practical biometric system applications.