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Symmetric hash functions for secure fingerprint biometric systems

机译:用于安全指纹生物识别系统的对称哈希函数

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Securing biometrics databases from being compromised is an important research challenge that must be overcome in order to support widespread use of biometrics based authentication. In this paper we present a novel method for securing fingerprints by hashing the fingerprint minutia and performing matching in the hash space. Our approach uses a family of symmetric hash functions and does not depend on the location of the (usually unstable) singular points (core and delta) as is the case with other methods described in the literature. It also does not assume a pre-alignment between the test and the stored fingerprint templates. We argue that these assumptions, which are often made, are unrealistic given that fingerprints are very often only partially captured by the commercially available sensors. The Equal Error Rate (EER) achieved by our system is 3%. We also present the performance analysis of a hybrid system that has an EER of 1.96% which reflects almost no drop in performance when compared to straight matching with no security enhancements. The hybrid system involves matching using our secure algorithm but the final scoring reverts to that used by a straight matching system.
机译:保护生物识别数据库不受破坏是一项重要的研究挑战,必须克服这一挑战,以支持基于生物识别的身份验证的广泛使用。在本文中,我们提出了一种通过散列指纹细节并在散列空间中执行匹配来保护指纹的新颖方法。我们的方法使用了一系列对称哈希函数,并且不依赖于(通常是不稳定的)奇异点(中心和增量)的位置,就像文献中描述的其他方法一样。它还不假定测试和存储的指纹模板之间存在预先对齐。我们认为,鉴于指纹通常只能通过商用传感器部分捕获,因此经常做出的这些假设是不现实的。我们的系统实现的平均错误率(EER)为3%。我们还介绍了EER为1.96%的混合系统的性能分析,与没有安全增强功能的直接匹配相比,该性能几乎没有下降。混合系统涉及使用我们的安全算法进行​​匹配,但最终得分将恢复为直接匹配系统所使用的得分。

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