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A fuzzy vault implementation for securing revocable iris templates

机译:用于保护可撤销虹膜模板的模糊保险库实施

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In recent years biometric cryptosystem evolved as a means for solving key management issues as well as protecting biometric templates. The fuzzy vault is a well known cryptotographic construction well suited for biometric systems. It has been studied theoretically as well as practically implemented in biometric systems using different biometric traits. When implemented in iris-based biometric system, the fuzzy vault faces two main challenges: 1) it requires an unordered set for successful implementation, and 2) it needs to deal with intra-class variations. In this paper, we implement a fuzzy vault based on the iris templates. A modified fuzzy vault resolves the issue of unordered set and error correction coding is used to deal with intra-class variations. An iris shuffling algorithm is also integrated into the system to ensure revocability. The proposed structure can be integrated with existing databases using binary iris templates and hence does not require the redesign of the biometric authentication system. Revocability ensures that even if the system is compromised new templates can be issued without compromising privacy of the individuals. The system is evaluated using the CASIA database and results show that the system is successful in ensuring security and revocability of the iris templates without compromising the performance
机译:近年来,生物识别密码系统发展成为一种解决关键管理问题以及保护生物识别模板的方法。模糊库是一种众所周知的密码结构,非常适合于生物识别系统。在使用不同生物特征的生物特征系统中,已经在理论上和实践上进行了研究。当在基于虹膜的生物识别系统中实现时,模糊库面临两个主要挑战:1)它需要无序集才能成功实现,以及2)它需要处理类内变异。在本文中,我们基于虹膜模板实现了一个模糊库。改进的模糊库解决了无序集的问题,纠错编码用于处理类内变异。虹膜改组算法也集成到系统中,以确保可撤销性。所提出的结构可以使用二进制虹膜模板与现有数据库集成,因此不需要重新设计生物特征认证系统。可撤销性确保即使系统受到损害,也可以在不损害个人隐私的情况下发布新模板。该系统使用CASIA数据库进行了评估,结果表明该系统在确保虹膜模板的安全性和可撤销性的同时,不影响性能的情况下取得了成功

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