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GREYC-Hashing: Combining biometrics and secret for enhancing the security of protected templates

机译:GREYC哈希:将生物识别技术和机密信息相结合以增强受保护模板的安全性

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摘要

Template protection is a crucial issue in biometrics. Many algorithms have been proposed in the literature among secure computing approaches, crypto-biometric algorithm and feature transformation schemes. The BioHashing algorithm belongs to this last category and has very interesting properties. Among them, we can cite its genericity since it could be applied on any biometric modality, the possible cancelability of the generated BioCode and its efficiency when the secret is not stolen by an impostor. Its main drawback is its weakness face to a combined attack (false acceptance with the stolen secret scenario). In this paper, we propose a transformation-based biometric template protection scheme as an improvement of the BioHashing algorithm where the projection matrix is generated by combining the secret and the biometric data. Experimental results on three biometric modalities, namely digital fingerprint, finger knuckle print and hands vein images, show the benefits of the proposed method face to attacks while keeping a good efficiency. (C) 2019 Elsevier B.V. All rights reserved.
机译:模板保护是生物识别技术中的关键问题。文献中已经提出了许多算法,其中包括安全计算方法,密码生物学算法和特征转换方案。 BioHashing算法属于最后一类,并且具有非常有趣的属性。其中,我们可以引用它的通用性,因为它可以应用于任何生物特征识别方式,所生成的BioCode可能的可取消性以及在机密者未窃取机密时其效率。它的主要缺点是面对联合攻击的弱点(在被盗的秘密情况下被错误接受)。在本文中,我们提出了一种基于变换的生物特征模板保护方案,作为对生物哈希算法的改进,该算法通过组合秘密和生物特征数据生成投影矩阵。在三种生物识别方式上的实验结果,即数字指纹,指节指纹和手静脉图像,表明了该方法面对攻击的好处,同时保持了良好的效率。 (C)2019 Elsevier B.V.保留所有权利。

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