Seeded Ising Model and Distributed Biometric Template Storage and Matching

It is known that a variant of Ising model, called Seeded Ising Model, can be used to recover the information content of a biometric template from a fraction of information therein. The method consists in reconstructing the whole template, which is called the intruder template in this paper, using only a small portion of the given template, a partial template. This reconstruction method may pose a security threat to the integrity of a biometric identity management system. In this paper, based on the Seeded Ising Model, we present a systematic analysis of the possible security breach and its probability of accepting the intruder templates as genuine. Detailed statistical experiments on the intruder match rate are also conducted under various scenarios. In particular, we study (1) how best a template is divided into several small pieces called partial templates, each of which is to be stored in a separate silo; (2) how to do the matching by comparing partial templates in the locked-up silos, and letting only the results of these intra-silo comparisons be sent to the central tallying server for final scoring without requiring the whole templates in one location at any time.     

A dexterous feature selection artificial immune system algorithm for keystroke dynamics

The main problem in security protecting the computer or resources from intruders. The password and username are the most common means to provide security. But this method has many loop holes such as password sharing, shoulder surfing, brute-force attack, dictionary attack, guessing, and many more. Keystroke dynamics is one popular and inexpensive behavioral biometric technology, which identifies the authenticity of a user when the user is working via a keyboard. Keystroke features like dwell time and flight time of every user are evaluated in this paper by preprocessing techniques such as Hausdroff timing, mean, median, and standard deviation. The artificial immune system is used for feature selection, and comparison between preprocessing techniques is shown.     

一种基于无证书生物特征数据的签名方案

在基于ID的无证书签名方案的基础上,通过模糊提取器获取生物特征信息来构造密钥,结合CL-PKC私钥生成原理,提出了一种基于生物特征的无证书签名方案.新方案在随机预言模型下是可证安全的,而且能够抵抗适应性选择消息攻击和ID攻击下的存在性伪造.该方案不仅解决了密钥托管问题而且与传统的方案相比具有较高的效率.     

利用生物特征数据的签名方案研究

研究了基于生物特征的密钥提取,利用模糊提取器将不可精确再生和非均匀分布的生物特征数据生成为可应用于经典密码体系的密钥,密钥的产生和用户的认证紧密结合,使认证和密钥产生这两个密码操作统一在一个密钥原语中实现.并将生物特征数据生成的密钥应用于短签名等经典的数字签名方案,从而达到更高的安全性和实用性.     

基于2DPCA的眉毛识别方法研究

分析了人类的眉毛作为一种独立生物特征进行身份鉴别的可能性,提出了一种基于2DPCA的眉毛识别方法,比较了2DPCA和PCA对眉毛识别的结果.通过对109人的眉毛数据库的分析,分别研究了2DPCA和PCA方法在眉毛识别中识别率和信息阈值之间,识别率与特征个数之间,识别率与图像尺寸之间的关系,以及它们对时间和空间的需求.实验结果表明,利用2DPCA方法进行眉毛识别在训练时间和识别率上明显优于PCA方法,识别率最高可达97.62%.     

A novel chaotic stream cipher and its application to palmprint template protection

Based on a coupled nonlinear dynamic filter (NDF), a novel chaotic stream cipher is presented in this paper and employed to protect palmprint templates. The chaotic pseudorandom bit generator (PRBG) based on a coupled NDF, which is constructed in an inverse flow, can generate multiple bits at one iteration and satisfy the security requirement of cipher design. Then, the stream cipher is employed to generate cancelable competitive code palmprint biometrics for template protection. The proposed cancelable palmprint authentication system depends on two factors: the palmprint biometric and the password/token. Therefore, the system provides high-confidence and also protects the user's privacy. The experimental results of verification on the Hong Kong PolyU Palmprint Database show that the proposed approach has a large template re-issuance ability and the equal error rate can achieve 0.02%. The performance of the palmprint template protection scheme proves the good practicability and security of the proposed stream cipher.     

Object Selection as a Biometric

The use of eye movement as a biometric is a new biometric technology that is now in competition with many other technologies such as the fingerprint, face recognition, ear recognition and many others. Problems encountered with these authentication methods such as passwords and tokens have led to the emergence of biometric authentication techniques. Biometric authentication involves the use of physical or behavioral characteristics to identify people. In biometric authentication, feature extraction is a very vital stage, although some of the extracted features that are not very useful may lead to the degradation of the biometric system performance. Object selection using eye movement as a technique for biometric authentication was proposed for this study. To achieve this, an experiment for collecting eye movement data for biometric purposes was conducted. Eye movement data were measured from twenty participants during choosing and finding of still objects. The eye-tracking equipment used was able to measure eye-movement data. The model proposed in this paper aimed to create a template from these observations that tried to assign a unique binary signature for each enrolled user. Error correction is used in authenticating a user who submits an eye movement sample for enrollment. The XORed Biometric template is further secured by multiplication with an identity matrix of size (n × n). These results show positive feedback on this model as individuals can be uniquely identified by their eye movement features. The use of hamming distance as additional verification helper increased model performance significantly. The proposed scheme has a 37% FRR and a 27% FAR based on the 400 trials, which are very promising results for future improvements.     

一种基于TD-ERCS的生物特征密钥产生算法

提出了一种新的思路,即由生物特征直接生成系统所需的密钥,从而降低了系统的成本和复杂性,并方便用户操作.为了保证该方法的安全性,采用改进后的切延迟椭圆反射腔混沌系统（TD-ERCS）对生物特征进行处理.实验结果表明该算法具有极高的运算速度,良好的生物特征敏感性、抗碰撞性和随机性,可实际用于生物特征密码系统. 关键词： 混沌 切延迟椭圆反射腔系统 生物特征密码系统 密钥产生算法     

Impact of NIR wavelength lighting in image acquisition on finger vein biometric system effectiveness

Finger vein biometric systems become increasingly more popular because they offer higher security comparing to other authentication solutions with respect to positive persons experience. Those systems operate on near infrared light (NIR) in wavelength range from around 700 to 1000 nm, however dedicated research to determine impact of NIR lighting on biometric system effectiveness has not been conducted and presented in the literature ever before. In this paper the study of correlation between wavelengths in NIR spectra and effectiveness of person identification in a biometric system is presented. To achieve that goal, a new model of image acquisition system allowing change of light wavelengths has been created and NIR finger vein dataset containing 11 556 images was established. Furthermore, this model was used to perform experimental work and proof that some NIR wavelengths better suit for vein patterns acquisition, allowing to increase the recognition effectiveness of finger vein biometric systems.