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基于模糊金库的多生物特征加密系统的一种新方法

A Novel Technique for Multi Biometric Cryptosystem Using Fuzzy Vault.

机构信息

Department of CSE, P. A. College of Engineering and Technology, Pollachi, Tamilnadu, India.

出版信息

J Med Syst. 2019 Mar 21;43(5):112. doi: 10.1007/s10916-019-1220-x.

Abstract

Biometric authentication is the process of recognizing a person by means of his\her psychological or behavioral traits. One of the most important issues faced by the biometric system developer is to protect the template obtained from the biometric of a person. Unimodal biometric system has some drawbacks such as noisy data, interclass variations and spoof attack. Multimodal biometric system has been developed to address the boundaries of unimodal biometric system and increase the security of template. In this paper, template security analysis of multimodal biometric system based of fingerprint and palmprint is proposed and implemented. Fuzzy vault scheme is employed to protect both the fingerprint and palmprint template. At enrollment, image processing techniques such as image enhancement, segmentation and bottom-hat filtering are applied on both the biometric to improve the quality and subsequently the most important features are extracted. Extracted features are concatenated. Combined features along with secret key are utilized to generate the database in the vault. During authentication, query images are sent as an input with the stored template to recover the key. Experimental results are shown that the proposed multi biometrics system performs well than the other methods considered for comparison.

摘要

生物特征认证是通过个人的心理或行为特征来识别他/她的过程。生物识别系统开发人员面临的最重要问题之一是保护从个人生物特征获得的模板。单模态生物识别系统存在一些缺点,例如数据噪声、类内变化和欺骗攻击。多模态生物识别系统已经被开发出来以解决单模态生物识别系统的局限性,并提高模板的安全性。在本文中,提出并实现了基于指纹和掌纹的多模态生物识别系统的模板安全分析。模糊金库方案被用于保护指纹和掌纹模板。在注册时,对两种生物特征进行图像处理技术,如图像增强、分割和底部帽滤波,以提高质量,随后提取最重要的特征。提取的特征被连接。将组合特征和秘密密钥一起用于在金库中生成数据库。在认证过程中,将查询图像作为输入与存储的模板一起发送,以恢复密钥。实验结果表明,所提出的多生物识别系统的性能优于其他考虑的方法。

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