Asymmetric Remote Biometric Authentication using Zero-Knowledge Proof

本文提出了一种新的安全远程生物特征认证方法，防止生物特征被泄露。这个想法是基于一个被称为零知识证明的公钥加密协议，它允许用户在不泄露数据的情况下证明她确实拥有有效的生物识别数据。因此，该方案不存在泄露生物特征数据的风险。即使恶意管理员具有访问私有数据库的特权，他也无法学习私有模板。基于实验实现的估计表明，私有欧几里得距离方案在接受和拒绝错误方面比私有余弦着色方案具有更好的准确性，但它需要大约5/2 NL开销来评估由l位整数组成的n维特征向量。

In this study, a new method for secure remote biometric authentication preventing the vulnerability of compromised biometrics is presented. The idea is based on a public-key cryptographical protocol, referred as Zero-knowledge Proof, which allows a user to prove that she has surely a valid biometric data without revealing the data. Hence, the scheme is free from the risk of disclosure of biometric data. Even if a malicious administrator has a privilege access to the private database, it is infeasible for him to learn the private template.The estimation based on the experimental implementation shows that the private Euclidean distance scheme archives better accuracy in terms of false acceptance and rejection than the private cosine coloration scheme, but it requires about 5/2 NL overhead to evaluate N-dimension feature vectors consisting of L-bit integers.