Generating cancelable fingerprint templates
Generating cancelable fingerprint templates
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DOI：
10.1109/tpami.2007.1004
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发表时间：
2007-04-01
影响因子：
23.6
通讯作者：
Bolle, Ruud M.
中科院分区：
文献类型：
--
作者：
Ratha, Nalini K.;Chikkerur, Sharat;Bolle, Ruud M.
与传统的密码和令牌身份验证方案相比，基于生物特征的身份验证系统具有明显的可用性优势。然而，生物识别技术引发了一些隐私问题。生物特征与用户永久关联，不能更改。因此，如果生物识别标识符被泄露，它将永远丢失，并且可能对使用该生物识别的每个应用程序都是如此。此外，如果在多个应用程序中使用相同的生物特征，则可以通过交叉匹配生物特征数据库跟踪用户从一个应用程序到下一个应用程序。在本文中，我们展示了几种从指纹图像中生成多个可取消标识符的方法来克服这些问题。从本质上讲，通过发布一个新的转换“密钥”，可以为用户提供尽可能多的生物识别标识符。标识符可以在受到威胁时被取消和替换。我们从经验上比较了几种算法的性能，如笛卡尔变换、极坐标变换和曲面折叠变换的细节位置。通过多个实验证明，我们可以实现生物特征数据库的可撤销性和防止交叉匹配。通过证明从转换版本中恢复原始生物识别标识符与随机猜测在计算上一样困难，也表明了转换是不可逆的。基于这些实证结果和理论分析，我们得出结论，特征级可取消生物特征构建在大型生物特征部署中是可行的。
Biometrics-based authentication systems offer obvious usability advantages over traditional password and token-based authentication schemes. However, biometrics raises several privacy concerns. A biometric is permanently associated with a user and cannot be changed. Hence, if a biometric identifier is compromised, it is lost forever and possibly for every application where the biometric is used. Moreover, if the same biometric is used in multiple applications, a user can potentially be tracked from one application to the next by cross-matching biometric databases. In this paper, we demonstrate several methods to generate multiple cancelable identifiers from fingerprint images to overcome these problems. In essence, a user can be given as many biometric identifiers as needed by issuing a new transformation "key." The identifiers can be cancelled and replaced when compromised. We empirically compare the performance of several algorithms such as Cartesian, polar, and surface folding transformations of the minutiae positions. It is demonstrated through multiple experiments that we can achieve revocability and prevent cross-matching of biometric databases. It is also shown that the transforms are noninvertible by demonstrating that it is computationally as hard to recover the original biometric identifier from a transformed version as by randomly guessing. Based on these empirical results and a theoretical analysis we conclude that feature-level cancelable biometric construction is practicable in large biometric deployments.