基于知识签名的可取消声纹模板

Wenhua Xu, Qianhua He, Yanxiong Li, Tao Li
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引用次数: 28

摘要

基于生物特征的身份验证可以为用户身份提供强有力的安全保证,但也会产生与模板安全性相关的其他问题。如何防止模板被滥用,如何保护好用户的隐私是一个重要的问题。本文提出了一种基于知识签名的方法来解决这些问题,该方法提供了一个可取消的模板。在服务器中只存储生物特征的不可逆转的转换版本,无法获取原始数据,因此可以很好地保护用户的隐私。而且,与其他可取消模板不同的是,它只需要密钥和生物特征之间的非紧密关联,即使密钥被公开,原始生物特征也不会被披露。实验结果表明,该方法是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cancelable Voiceprint Templates Based on Knowledge Signatures
Biometric-based authentication can provide strong safety guarantee of user identity, but creates other concerns pertaining to template security. How to prevent the templates from being abused, and how to protect the users' privacy well are important problems. This paper proposes an approach based on knowledge signatures to solve these problems, which provides a cancelable template. Only a non-invertible transformed version of the biometrics is stored in the server, and the original data can't be obtained, so the users' privacy can be protected well. Moreover, distinguished with other cancelable templates, it only needs an incompact association between the key and the biometrics feature, even if the key is disclosed, the original biometrics feature wouldn't be revealed. The experimental results show that the proposed approach is practical.
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