Fuzzy Vault for Face Based Cryptographic Key Generation

Yongjin Wang, K. Plataniotis
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引用次数: 75

Abstract

This paper presents a method for changeable cryptographic key generation using face biometrics signal. A previously introduced scheme, fuzzy vault, is utilized for secure binding of randomly generated key with extracted biometrics features. The major technical difficulty is to map noisy biometrics representation to the exactly correct key. In this paper, the proposed method is based on 2-dimensional quantization of distance vectors between biometrics features and pairs of random vectors. A windowing process is applied to tolerate the variations of biometrics signals. Further, we also introduce a two-factor scheme, where the quantized distance vectors are generated with user-dependent random vectors. By integrating a second factor, both the biometrics and the key are changeable, and zero error rate can be obtained.
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基于人脸的密码密钥生成模糊保险库
提出了一种利用人脸生物特征信号生成可变密码密钥的方法。之前介绍的模糊保险库方案用于将随机生成的密钥与提取的生物特征进行安全绑定。主要的技术难点是将有噪声的生物特征表示映射到完全正确的密钥。本文提出的方法是基于生物特征特征与随机向量对之间的距离向量的二维量化。采用开窗处理来容忍生物特征信号的变化。此外,我们还引入了一种双因子方案,其中量化的距离向量由用户相关的随机向量生成。通过对第二因子的积分,使得生物特征和密钥都是可变的,从而实现了零错误率。
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