Protecting Face Biometric Data on Smartcard with Reed-Solomon Code
Protecting Face Biometric Data on Smartcard with Reed-Solomon Code
复制标题
使用 Reed-Solomon 代码保护智能卡上的人脸生物识别数据
DOI：
10.1109/cvprw.2006.164
复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
P. Yuen
中科院分区：
文献类型：
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作者：
Yi C. Feng;P. Yuen
本文解决了SmartCard上的生物识别安全问题，并提出了一种保护面部生物识别数据免受攻击的新方法。提出的方法是基于Reed-Solomon代码开发的，具有两个修改。首先，为解决图像变化问题，使用有界距离编码算法来减少课堂内距离。其次，由于面部特征向量的尺寸相对较大，因此我们将特征向量分为较小的段。这样，我们发现它不仅会影响性能，而且会影响编码算法的安全性。本文还提供了理论分析。选择了两个最受欢迎的基于外观的方法，即特征表和渔夫来构建特征向量和ORL数据库进行评估。在本特征系统中，提出的算法提供了120位的安全级别，可接受的错误率约为3％。在Fisherface System中，拟议的算法提供了62位的安全级别，错误率相等约5％。结果与本本本特征表和渔夫的性能相当。
This paper addresses the biometric security problem on smartcard and proposes a new method to protect face biometric data against attack. The proposed method is developed based on the Reed-Solomon codes, with two modifications. First, to handle the image variations problem, a bounded distance encoding algorithm is used to reduce the within-class distance. Second, since the dimension of the face feature vector is relatively large, we divide the feature vector into smaller segment. In this way, we found that it will not only affect the performance, but also the security of the encoding algorithm. A theoretical analysis is also given in this paper. Two most popular appearance-basedmethods, namely, Eigenface and Fisherface, are selected to construct the feature vector and ORL database is used for evaluation. In Eigenface system, the proposed algorithm offers a security level of 120 bits, with an acceptable error rate of around 3%. In Fisherface system, the proposed algorithm offers a security level of 62 bits, with equal error rate around 5%. The results are comparable with performance of Eigenface and Fisherface without protection.
基于特征脸的人脸建模与识别
DOI：
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发表时间：
2003
期刊：
IPSJ SIG Technical Reports Vol. CVIM-139
影响因子：
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作者：
T.;Shakunaga;F.;Sakaue;Y.;Matsubara
通讯作者：
Matsubara