3D Fuzzy Vault Based on Palmprint

Hailun Liu, Dongmei Sun, Ke Xiong, Z. Qiu
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引用次数: 7

Abstract

Biometric cryptosystem has emerged as a promising solution in information security. Fuzzy vault is a widely accepted scheme that binding biometric data and cryptography effectively. In vault encoding, random chaff points which are not on the polynomial are added to protect genuine points. In vault decoding, query biometric data is generated to retrieve the genuine points by measuring the distance between the registered data and query data. However, because of the within-class differences and randomness of chaff points, it is difficult to distinguish the genuine data from chaff data. This paper proposes a novel 3D fuzzy vault scheme that selects unused data from template feature vector and inserts it into the genuine points. In our scheme, every point in the vault has three dimensions, two of which could be used for distance measurement. The precision of the data matching is improved by the new inserted data and genuine points could be recognized more accurately. Experimental results based on HA-BJTU database show the better performances compared to traditional fuzzy vault.
基于掌纹的三维模糊金库
生物识别密码系统已成为信息安全领域一种很有前途的解决方案。模糊保险库是一种被广泛接受的将生物特征数据与密码学有效结合的方案。在vault编码中,加入了不在多项式上的随机箔条点来保护真点。在vault解码中,通过测量注册数据与查询数据之间的距离,生成查询生物特征数据来检索真实点。然而,由于箔条点的类内差异和随机性,很难区分真实数据和箔条数据。本文提出了一种新的三维模糊拱顶方案,从模板特征向量中选择未使用的数据,并将其插入到真实点中。在我们的方案中,拱顶中的每个点都有三个维度,其中两个维度可以用于距离测量。新插入的数据提高了数据匹配的精度,可以更准确地识别出真实点。基于HA-BJTU数据库的实验结果表明,与传统模糊拱顶相比,该算法具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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