Lee Youn Joo, Park Kang Ryoung, Lee Sung Joo, Bae Kwanghyuk, Kim Jaihie
School of Electricaland Electronic Engineering, Biometrics Engineering Research Center, Yonsei University, Seoul 120-749, Korea.
IEEE Trans Syst Man Cybern B Cybern. 2008 Oct;38(5):1302-13. doi: 10.1109/TSMCB.2008.927261.
Cryptographic systems have been widely used in many information security applications. One main challenge that these systems have faced has been how to protect private keys from attackers. Recently, biometric cryptosystems have been introduced as a reliable way of concealing private keys by using biometric data. A fuzzy vault refers to a biometric cryptosystem that can be used to effectively protect private keys and to release them only when legitimate users enter their biometric data. In biometric systems, a critical problem is storing biometric templates in a database. However, fuzzy vault systems do not need to directly store these templates since they are combined with private keys by using cryptography. Previous fuzzy vault systems were designed by using fingerprint, face, and so on. However, there has been no attempt to implement a fuzzy vault system that used an iris. In biometric applications, it is widely known that an iris can discriminate between persons better than other biometric modalities. In this paper, we propose a reliable fuzzy vault system based on local iris features. We extracted multiple iris features from multiple local regions in a given iris image, and the exact values of the unordered set were then produced using the clustering method. To align the iris templates with the new input iris data, a shift-matching technique was applied. Experimental results showed that 128-bit private keys were securely and robustly generated by using any given iris data without requiring prealignment.
密码系统已广泛应用于许多信息安全应用中。这些系统面临的一个主要挑战是如何保护私钥不被攻击者获取。最近,生物特征密码系统作为一种通过使用生物特征数据来隐藏私钥的可靠方法被引入。模糊保险库是一种生物特征密码系统,可用于有效保护私钥,并仅在合法用户输入其生物特征数据时才释放私钥。在生物特征系统中,一个关键问题是在数据库中存储生物特征模板。然而,模糊保险库系统不需要直接存储这些模板,因为它们通过使用密码学与私钥相结合。以前的模糊保险库系统是通过使用指纹、面部等设计的。然而,尚未有人尝试实现使用虹膜的模糊保险库系统。在生物特征应用中,众所周知,虹膜比其他生物特征模态更能区分不同的人。在本文中,我们提出了一种基于局部虹膜特征的可靠模糊保险库系统。我们从给定虹膜图像的多个局部区域提取了多个虹膜特征,然后使用聚类方法生成无序集的确切值。为了将虹膜模板与新输入的虹膜数据对齐,应用了移位匹配技术。实验结果表明,使用任何给定的虹膜数据都能安全、稳健地生成128位私钥,且无需预先对齐。