针对已有指纹密钥隐藏方法的不足,提出了一种新的基于指纹的密钥隐藏方案,为了充分利用指纹图像细节点以及细节点周围的纹理信息,采用了一种新定义的指纹模板:细节点纹理串模板,这种密钥隐藏方案也就称为细节点纹理串密钥隐藏方案.在此方案中,首先提取指纹的细节点集合,然后在每个细节点周围使用Gabor滤波器滤波,以提取细节点周围的指纹纹理信息,细节点集合和每个细节点对应的纹理信息共同构成细节点纹理串模板.然后,用(n,k)秘密分割方法将对称加密系统或PKI产生的密钥分成n份秘密值,每份秘密值以保密的方式存储在细节点对应的纹理串中,只有当询问指纹能恢复出至少是份秘密时,才可以恢复出原密钥.在指纹数据库FVC2002 DB1和DB2上的实验表明,一指纹用于隐藏密钥,另一指纹用于恢复密钥的情况下,该方案的等错率(equal error rate,EER)为1％～2.2％,优于模糊盖子密钥隐藏方案.安全性分析表明,该方案有效地保护了密钥以及指纹模板信息,安全度高于模糊盖子方案.%In view of shortage of the existing fingerprint-based key hiding method, a new key hiding scheme based on fingerprint is proposed, which fully uses the information of minutiae set and the texture information around every minutia, depending on a new fingerprint model: minutiae texture strings model. The scheme is called minutiae texture strings key hiding scheme. In this scheme, minutiae set is extracted from fingerprint firstly, and Gabor filter is then used to the area around every minutia to extract texture information. Minutiae set and texture information around every minutia construct the minutiae texture strings model. Secret key generated by a symmetric encryption system or distributed by PKI is divided into n shares by a (n, k) secret sharing algorithm, which are then hidden by minutiae texture strings secretly. Query fingerprint can only recover the hidden key when at least k shares of key are retrieved. Experiments are made on FVC2002 DB1 and DB2, in which one fingerprint is used to hide key and another fingerprint is used to recover the key. Equal error rate (EER) of the scheme is no more than 1%~2. 2%, which is better than that of normal fuzzy vault. Security analysis of the scheme shows that information of the key and the fingerprint model is protected effectively, with security higher than that of normal fuzzy vault schemes.
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