Alignment-free cancelable fingerprint template design: A densely infinite-to-one mapping (DITOM) approach

Registration-based cancelable template schemes rely on accurate fingerprint image alignment, which is very difficult to achieve. In this paper, by exploiting pair-minutiae vectors, we develop a lightweight, alignment-free scheme for generating cancelable fingerprint templates. The proposed mathematical model is based on a densely infinite-to-one mapping (DITOM) aiming to achieve the non-invertible property. The transformation designed describes the intersection of a collection of hyperplanes and effectively realizes infinite-to-one mapping. The proposed scheme has the properties of non-invertibility, revocability and multiple template independence. Evaluation of the proposed scheme over FVC2002 DB1, DB2 and DB3 shows that the new method exhibits satisfactory performance compared to existing methods.     

Pair-polar coordinate-based cancelable fingerprint templates

Fingerprint-based authentication has been widely implemented, however, security and privacy of fingerprint templates still remain an issue. Some schemes have been proposed to protect fingerprint templates, such as the design of cancelable fingerprint templates. Yet, most of the existing schemes rely on accurate fingerprint image registration, which is very hard to achieve, especially considering the need to avoid storing any information related to the raw fingerprint features. In this paper, a pair-polar coordinate-based template design method is developed which does not need registration. The proposed scheme explores the relative relationship of minutiae in a rotation- and shift-free pair-polar framework. A many-to-one mapping is applied to ensure the non-invertible recovery of raw templates. A random translation parameter is introduced to further distort the minutia distribution. Under various scenarios, the proposed scheme is evaluated using the public databases, FVC2002DB1, FVC2002DB2 and FVC2002DB3. The experiment results show that the new method satisfies the template protection requirements and the performance degradation caused by the transformation is very low.     

Alignment-free cancelable fingerprint templates based on local minutiae information.

To replace compromised biometric templates, cancelable biometrics has recently been introduced. The concept is to transform a biometric signal or feature into a new one for enrollment and matching. For making cancelable fingerprint templates, previous approaches used either the relative position of a minutia to a core point or the absolute position of a minutia in a given fingerprint image. Thus, a query fingerprint is required to be accurately aligned to the enrolled fingerprint in order to obtain identically transformed minutiae. In this paper, we propose a new method for making cancelable fingerprint templates that do not require alignment. For each minutia, a rotation and translation invariant value is computed from the orientation information of neighboring local regions around the minutia. The invariant value is used as the input to two changing functions that output two values for the translational and rotational movements of the original minutia, respectively, in the cancelable template. When a template is compromised, it is replaced by a new one generated by different changing functions. Our approach preserves the original geometric relationships (translation and rotation) between the enrolled and query templates after they are transformed. Therefore, the transformed templates can be used to verify a person without requiring alignment of the input fingerprint images. In our experiments, we evaluated the proposed method in terms of two criteria: performance and changeability. When evaluating the performance, we examined how verification accuracy varied as the transformed templates were used for matching. When evaluating the changeability, we measured the dissimilarities between the original and transformed templates, and between two differently transformed templates, which were obtained from the same original fingerprint. The experimental results show that the two criteria mutually affect each other and can be controlled by varying the control parameters of the changing functions.     

基于细节点投影的可撤销指纹模板生成算法

为了改善指纹模板保护算法的可撤销性、不可逆性等性能,设计了一种基于细节点投影的可撤销指纹模板生成算法.首先对指纹图像进行预处理,提取指纹的细节点特征,并筛选出采样半径范围内的有效细节点,然后对细节点进行直线投影,将投影后的向量映射到二维网格,生成固定长度的一维比特串,再结合用户PIN码生成可撤销指纹模板.在指纹数据库FVC2002-DB1和DB2上的实验结果表明,该算法不仅提高了指纹模板认证的稳定性,而且在可撤销性、不可逆性和安全性等方面均具有较好性能.     

基于细节点邻域信息的可撤销指纹模板生成算法

为了提高指纹模板算法的安全性等性能,设计了一种基于细节点邻域信息的可撤销指纹模板生成算法.首先对指纹图像进行预处理,提取指纹的细节点特征,然后采用改进的细节点描述子采样结构提取细节点邻域的纹线特征,最后结合用户PIN码生成指纹模板,同时结合贪婪算法设计了相应的指纹匹配算法.在指纹数据库FVC2002-DB1和DB2上的实验表明,该算法具有良好的认证性能,能较好地满足可撤销性、多样性和不可逆性,而且改进的采样结构在没有降低系统识别性能的情况下,进一步拓展了细节点描述子的采样结构方式.     

Fingerprint template protection with minutiae-based bit-string for security and privacy preserving

Recently, biometric template protection has received great attention from the research community due to the security and privacy concerns for biometric template. Although a number of biometric template protection methods have been reported, it is still a challenging task to devise a scheme which satisfies all of the four template protection criteria namely diversity, revocability, non-invertibility and performance. In this paper, a method is proposed to generate a revocable fingerprint template in terms of bit-string from a set of minutiae points via a polar grid based 3-tuple quantization technique. Two merits of the proposed method are outlined, namely alignment-free and performance. Four publicly available benchmark datasets: FVC2002 DB1, DB2 and FVC2004 DB1, DB2 are used to evaluate the performance of the proposed method. Besides, the diversity, revocability, non-invertibility criteria are also analyzed.     

安全高效的可撤销指纹模板构造

指纹特征加密是生物特征识别技术中最为活跃的研究领域之一.然而指纹特征是人体固有的特征,具有唯一性与终身不变性,一旦识别系统中的用户指纹模板丢失,将是永久性的.为了避免用户指纹模板丢失,基于巴特沃斯低通滤波器原型,设计了一组不可逆转换函数,将用户原始指纹模板转换为可撤销指纹模板,不同识别系统中存储的可撤销指纹模板具有互异性与不可逆性,进而有效规避原始指纹模板的不变性与公开性所带来的安全隐患.匹配精度、不可逆性、转换速度等方面的实验分析表明,所构造可撤销指纹模板方案在认证效率、安全性、计算效率等方面具有良好性能.     

基于LGBP与Bloom滤波器的可撤销掌纹模板生成方法

为了实现对用户生物特征信息的有效保护,提高掌纹身份认证系统的安全性,提出一种掌纹可撤销模板生成方法。首先通过Gabor滤波器获得掌纹数据不同方向、不同尺度的幅值特征,对其提取局部均匀模式LBP特征,然后将二值化的特征直方图序列使用Bloom滤波器进行多对一映射,最后进行不可逆变换,得到可撤销掌纹模板。理论分析和实验结果表明,该方法不仅可以有效保护掌纹特征,而且在密钥丢失时,也具有较高的识别率。     

Face Templates Encryption Technique Based on Random Projection and Deep Learning

Cancellable biometrics is the solution for the trade-off between two concepts: Biometrics for Security and Security for Biometrics. The cancelable template is stored in the authentication system’s database rather than the original biometric data. In case of the database is compromised, it is easy for the template to be canceled and regenerated from the same biometric data. Recoverability of the cancelable template comes from the diversity of the cancelable transformation parameters (cancelable key). Therefore, the cancelable key must be secret to be used in the system authentication process as a second authentication factor in conjunction with the biometric data. The main contribution of this paper is to tackle the risks of stolen/lost/shared cancelable keys by using biometric trait (in different feature domains) as the only authentication factor, in addition to achieving good performance with high security. The standard Generative Adversarial Network (GAN) is proposed as an encryption tool that needs the cancelable key during the training phase, and the testing phase depends only on the biometric trait. Additionally, random projection transformation is employed to increase the proposed system’s security and performance. The proposed transformation system is tested using the standard ORL face database, and the experiments are done by applying different features domains. Moreover, a security analysis for the proposed transformation system is presented.     

基于安全概略的可撤销掌纹模板生成算法

为了有效改进掌纹模板生成算法的识别率和安全性等性能,提出一种基于安全概略的可撤销掌纹模板生成算法。首先提取掌纹图像不同方向、不同尺度的Gabor幅值特征,并通过主成分分析（PCA）算法对其进行降维;然后将加密后的特征向量与BCH码异或融合,得到基于安全概略的可撤销掌纹模板。对比实验表明,该算法具有良好的识别性能,能较好地满足可撤销性、多样性和不可逆性,即便在单密钥丢失的情况下,也具有较高的识别率。     

一种有效的指纹图像方向滤波增强算法 *

方向滤波是沿着指纹纹线方向滤波的方法。一种方向滤波算法的有效性主要依赖于指纹图像方向估计的准确性和滤波模板构造的合理性。首先利用对低质量指纹图像鲁棒性较高的掩膜法估计点方向 ,并将点方向转换为块方向 ;然后使用八个方向的平滑滤波模板和锐化滤波模板 ,对指纹图像滤波进行增强 ;最后对增强后的指纹图像二值化。通过对 FVC2000指纹数据库 DB2中的指纹图像作增强处理 ,表明该算法增强效果较好。     

Extraction and fusion of partial face features for cancelable identity verification

In this paper, we propose to extract localized random features directly from partial face image matrix for cancelable identity verification. Essentially, the extracted random features consist of compressed horizontal and vertical facial information obtained from a structured projection of the raw face images. For template security reason, the face appearance information is concealed via averaging several templates over different transformations. The match score outputs of these cancelable templates are then fused through a total error rate minimization. Extensive experiments were carried out to evaluate and benchmark the performance of the proposed method based on the AR, FERET, ORL, Sheffield and BERC databases. Our empirical results show encouraging performances in terms of verification accuracy as well as satisfying four cancelable biometric properties.     

RP-LPP : a random permutation based locality preserving projection for cancelable biometric recognition

Biometrics are being increasingly used across the world, but it also raises privacy and security concerns of the enrolled identities. The main reason is due to the fact that biometrics are not cancelable and if compromised may give access to the intruder. Cancelable biometric template is a solution to this problem which can be reissued if compromised. In this paper, we suggest a simple and powerful method called Random Permutation Locality Preserving Projection (RP-LPP) for Cancelable Biometric Recognition. Here, we exploit the mathematical relationship between the eigenvalues and eigenvectors of the original biometric image and its randomly permuted version is exploited for carrying out cancelable biometric recognition. The proposed technique work in a cryptic manner by accepting the cancelable biometric template and a key (called PIN) issued to a user. The effectiveness of the proposed techniques is demonstrated on three freely available face (ORL), iris (UBIRIS) and ear (IITD) datasets against state-of-the-art methods. The advantages of proposed technique are (i) the classification accuracy remains unaffected due to cancelable biometric templates generated using random permutation, (ii) security and quality of generated templates and (iii) robustness across different biometrics. In addition, no image registration is required for performing recognition.

     

Cancelable fingerprint templates using minutiae-based bit-strings

It has become critical to protect biometric templates in the current biometric community. One way for doing this is using a cancelable biometric method, which transforms original biometric templates in a non-invertible way and uses those transformed templates to verify a person's identity. In this paper, we propose a new method to generate cancelable bit-strings (templates) from fingerprint minutiae. Our method is to provide a simple mean to generate cancelable templates without requiring for pre-alignment of fingerprints. The main idea is to map the minutiae into a predefined 3 dimensional array which consist of small cells and find out which cells include minutiae. To do this, we choose one of minutiae as a reference minutia and other minutiae are translated and rotated in order to map the minutiae into the cells based on the position and orientation of the reference minutia. After mapping, we set the cells in the 3D array to 1 if they include more than one minutia otherwise the cells are set to 0. A 1D bit-string is generated by sequentially visiting the cells in the 3D array. The order of the 1D bit-string is permuted according to the type of reference minutiae and user's PIN so that we can regenerate new templates when we need them. Finally, cancelable bit-strings are generated by changing the reference minutia into another minutia in turn. In the experiments, we evaluate our method using the FVC2004 database and show that the performance is better than that of a previous method.     

基于指纹的可撤销Fuzzy vault方案

Fuzzy vault是一种用生物特征保护密钥的加密框架,其主要缺点在于攻击者可以通过交叉比较同一用户的不同vault来获得生物模板的准确信息,从而可以破解vault。提出了一种使用基于指纹细节点的可撤销的变换模板作为生成vault的模板,保护不同密钥时采用不同变换模板,从而解决了这个问题。采用以巴特沃斯低通滤波器为核的函数组作为生成可撤销模板的变换函数。此外还使用了用户口令加密vault,从而进一步增强了被保护密钥的安全性。     

Situation awareness of cancelable biometric system

Recently, cancelable biometrics emerged as one of the highly effective methods of template protection. The concept behind the cancelable biometrics or cancelability is a transformation of a biometric data or extracted feature into an alternative form, which cannot be used by the imposter or intruder easily, and can be revoked if compromised. In this paper, we present a novel architecture for template generation in the context of situation awareness system in real and virtual applications. We develop a novel cancelable biometric template generation algorithm utilizing random biometric fusion, random projection and selection. Proposed random cross-folding method generate cancelable biometric template from multiple biometric traits. We further validate the performance of the proposed algorithm using a virtual multimodal face and ear database.     

Biometric template selection and update: a case study in fingerprints

A biometric authentication system operates by acquiring biometric data from a user and comparing it against the template data stored in a database in order to identify a person or to verify a claimed identity. Most systems store multiple templates per user in order to account for variations observed in a person's biometric data. In this paper we propose two methods to perform automatic template selection where the goal is to select prototype fingerprint templates for a finger from a given set of fingerprint impressions. The first method, called DEND, employs a clustering strategy to choose a template set that best represents the intra-class variations, while the second method, called MDIST, selects templates that exhibit maximum similarity with the rest of the impressions. Matching results on a database of 50 different fingers, with 200 impressions per finger, indicate that a systematic template selection procedure as presented here results in better performance than random template selection. The proposed methods have also been utilized to perform automatic template update. Experimental results underscore the importance of these techniques.     

基于自适应投影的指纹模板生成算法

针对现有指纹模板生成算法存在的准确性较低、安全性较差的问题,提出一种基于自适应投影的指纹模板生成算法。该算法将有效细节点对之间的距离垂直投影到自适应圆上,并对投影后的向量进行量化得到比特串。此外,为增强数据的安全性及隐私性,采用异或和随机索引置乱变换对比特串进行处理,最终生成指纹模板。在数据库FVC2002 DB1和DB2中的实验结果表明,该算法相较于对比算法,具有较高的准确性和安全性。     

PalmPhasor算法性能的理论分析

模板的安全性和隐私性是掌纹系统实际应用的关键问题,然而生物特征保护的多项指标通常相互冲突并且难以同时满足.作为解决上述冲突的一种可撤销掌纹编码算法,PalmPhasor实现了高效、安全的掌纹认证.建立了系统分析PalmPhasor性能的完整框架.为了便于具体分析,将情景分为4种情况,并且提供了支持相应分析的预备知识,包括辅助定理以及Gabor滤波掌纹图像实部和虚部分布特性.在统计学基础上建立的理论分析和实验结果均表明:即使在用户口令被盗的情况下,多方向分数级融合增强的PalmPhasor算法也可以同时有效地满足可撤销生物特征的4项指标.     

Dual-key-binding cancelable palmprint cryptosystem for palmprint protection and information security

Biometric cryptosystems and cancelable biometrics are both practical and promising schemes to enhance the security and privacy of biometric systems. Though a number of bio-crypto algorithms have been proposed, they have limited practical applicability because they lack of cancelability. Since biometrics are immutable, the users whose biometrics are stolen cannot use bio-crypto systems anymore. Cancelable biometric schemes are of cancelability; however, they are difficult to compromise the conflicts between the security and performance. By embedded a novel cancelable palmprint template, namely “two dimensional (2D) Palmprint Phasor”, the proposed palmprint cryptosystem overcomes the lack of cancelability in existing biometric cryptosystems. Besides, the authentication performance is enhanced when users have different tokens/keys. Furthermore, we develop a novel dual-key-binding cancelable palmprint cryptosystem to enhance the security and privacy of palmprint biometric. 2D Palmprint Phasor template is scrambled by the scrambling transformation based on the chaotic sequence that is generated by both the user's token/key and strong key extracted from palmprint. Dual-key-binding scrambling not only has more robustness to resist against chosen plain text attack, but also enhances the secure requirement of non-invertibility. 2D Palmprint Phasor algorithm and dual-key-binding scrambling both increase the difficulty of adversary's statistical analysis. The experimental results and security analysis confirm the efficiency of the proposed scheme.