生物特征识别技术发展与应用综述

生物特征识别技术是一种利用人体独一无二的生物特征进行身份识别的技术。介绍了当前生物特征识别技术的工作模式和发展现状,指出了生物特征识别技术的发展趋势,并对当前生物特征识别过程中面对的安全性进行了论述。     

浅谈计算机用户身份识别技术

人体生物特征具备了稳定性、惟一性的重要特性,比如指纹、虹膜、DNA等,因此计算机用户通过这些特征识别身份,可以极大地提高信息的安全程度。生物识别技术的核心是将实时观察到的生物特征跟存储于电脑、已登记的特征进行可靠性匹配,进而达到对比验证身份的目的,这种技术具备了可靠安全、方便快捷的优点。在本文中,笔者主要论述了生物识别技术的基础,生物识别身份的重要途径和方式吗,以及在计算机信息安防中的运用,并针对性地对多种身份识别技术进行了比较。     

在未来网络中大有作为的生物特征识别技术

本文分析了生物特征识别技术的应用领域和发展前景,作为一种身份识别手段,生物特征识别技术具有独特的优势,对信息和网络安全等有重要意义。     

现代生物特征识别技术发展综述

生物特征识别技术作为一种身份识别手段具有独特的优势,是近年来国际上的研究热点,对信息安全有重要意义.文章简单介绍了几种典型的生物特征(如指纹、人脸、虹膜等)和语音识别技术方法,对各种方法的特点作了比较说明,对生物特征识别技术的应用领域和发展首景作了较详尽的分析.     

刍议身份鉴别技术的发展

常见的身份鉴别技术有射频识别技术、指纹识别技术、人脸识别技术、说话人识别技术和虹膜识别技术等,射频识别技术是一种传统的身份鉴别技术,其他几种识别技术均为基于人体生物特征的识别技术.介绍了各项技术的发展过程、核心技术、优缺点和面临的技术挑战.     

浅谈虹膜识别系统的特点和优势

已有越来越多的人都承认现有基于智能卡、身份号和密码的身份识别系统无论从方便性或安全性已无法满足要求，因此生物特征识别技术就提供了一个较完善的解决方案。而基于虹膜的生物识别技术是一种新颖的身份鉴别技术，它高精度的识别准确度使其能够在众多识别技术中占有一席之地。本文将就虹膜与其它身份识别技术进行详细的比较。[编者按]     

基于多模态生物识别的安全身份认证技术

本文分析了传统身份认证方法在电子取证中存在的问题,突出了生物特征识别技术应用于电子取证中的优点。针对单模态生物特征技术存在识别精度不够等问题,提出了将多模态生物特征技术的安全身份认证的体系结构,并探讨了多种特征信息融合的方法。[编者按]     

基于HMM的步态身份识别

随着生物识别悄然兴起,生物识别技术逐渐成为新的身份识别技术。步态识别是生物特征识别技术的一个新兴子领域。文章就是将隐马尔可夫模型(HMM,HiddenMarkovModel)方法运用在步态身份识别中,并进行了其识别性能的研究。该文给出了一个基于HMM的步态身份识别方案,并进行了图像预处理,HMM参数训练和识别的研究,得出了一些有意义的结论。同时在中国科学院自动化研究所提供的CASIA步态数据库上进行了步态身份识别实验,实验结果表明:在侧面视角下采用此方法,具有较好的识别率。     

浅谈指纹统计资料识别技术的历史与发展

生物识别技术（Biometric Identification Technolosy）是利用人体生物特征进行身份认证的一种技术，是当今最先进和最可靠的识别技术之一。在众多生物识别技术中，指纹识别技术的发展历史最早，同时指纹识别技术也是最早通过计算机实现身份识别的手段，在今天它也是应用最为广泛的生物特征识别技术，是当之无愧的物证之首。     

人脸识别的市场和应用分析

生物识别技术是利用人体生物特征进行身份认证的一种技术,人脸识别以其完全非接触和直观的特点,成为生物识别当中颇受关注的识别方式之一。     

A review on performance,security and various biometric template protection schemes for biometric authentication systems

Identifying a person based on their behavioral and biological qualities in an automated manner is called biometrics. The authentication system substituting traditional password and token for authentication and relies gradually on biometric authentication methods for verification of the identity of an individual. This proves the fact that society has started depending on biometric-based authentication systems. Security of biometric authentication needs to be reviewed and discussed as there are multiple points related to integrity and public reception of biometric-based authentication systems. Security and recognition accuracy are the two most important aspects which must be considered while designing biometric authentication systems. During enrollment phase scanning of biometric data is done to determine a set of distinct biometric feature set known as biometric template. Protection of biometric templates from various hacking efforts is a topic of vital importance as unlike passwords or tokens, compromised biometric templates cannot be reissued. Therefore, giving powerful protection techniques for biometric templates and still at that very moment preparing great identification accuracy is a good research problem nowadays, as well as in the future. Furthermore, efficiency under non-ideal conditions is also supposed to be inadequate and thus needs special attention in the design of a biometric authentication system. Disclosure of various biometric traits in miscellaneous applications creates a severe compromise on the privacy of the user. Biometric authentication can be utilized for remote user authentication. In this case, the biometric data of users typically called templates are stored in a server. The uniqueness and stability of biometrics ended it useful over traditional authentication systems. But, a similar thing made the enduring harm of a user’s identity in biometric systems. The architecture of the biometric system leads to several hazards that lead to numerous security concerns and privacy threats. To address this issue, biometric templates are secured using several schemes that are categorized as biometric cryptosystems, cancelable biometrics, hybrid methods, Homomorphic Encryption, visual cryptography based methods. Biometric cryptosystems and cancelable biometrics techniques provide reliable biometric security at a great level. However, there persist numerous concerns and encounters that are being faced during the deployment of these protection technologies. This paper reviews and analyses various biometric template protection methods. This review paper also reflects the limitations of various biometric template protection methods being used in present times and highlights the scope of future work.

     

基于模糊逻辑的击键特征用户认证系统

为了增强用户身份认证机制的安全性,在传统的口令认证方式的基础上,提出了一种基于模糊逻辑的击键特征用户认证方法。该方法利用模糊逻辑对用户输入口令的键盘特征进行分析鉴别,并结合用户口令进行用户身份认证。该方法有效弥补了传统的口令机制易被攻击的缺点,有一定的实用性。     

Physimetric identification (Physi-ID)—Applying biometric concept in physical object identification

By relying on business intelligence technologies, services can be delivered to customers automatically by computer systems. To provide the right services to the right person, a methodology that precisely identifies a personal's identity must be in place. Biometrics offers a secure and reliable method for computerized personal identification and authentication. It accurately recognizes and determines the unique identity of a person based on her physiological and/or behavioral characteristics. In the case of physical objects, they may also be required to be identified automatically in order to provide additional services, such as at checkout counters of supermarkets or customs clearance checkpoints. Numerous crimes and business losses (e.g. counterfeit products) are related to mis-identification of physical objects. This paper introduces physimetric identification, an approach that applies the concept of biometrics for physical object identification. It addresses the problem through authenticating physical objects based on their unique physical and/or chemical characteristics. Apart from introducing the concept of physimetric identification, issues such as real applications, deployment considerations and limitations of the proposed technology will also be discussed.     

Biometrics in Identity Management Systems

Biometric technology - the automated recognition of individuals using biological and behavioral traits - has been presented as a natural identity management tool that offers "greater security and convenience than traditional methods of personal recognition." Indeed, many existing government identity management systems employ biometrics to assure that each person has only one identity in the system and that only one person can access each identity. Historically, however, biometric technology has also been controversial, with many writers suggesting that biometrics invade privacy, that specific technologies have error rates unsuitable for large-scale applications, or that the techniques "are useful to organizations that regulate the individual, but of little use where the individual controls identification and authorization." Here, I address these controversies by looking more deeply into the basic assumptions made in biometric recognition. I'll look at some example systems and delve into the differences between personal identity and digital identity. I'll conclude by discussing how those whose identity is managed with biometrics can manage biometric identity management.     

Secure-OSCAR中基于PKI的生物身份认证的设计

个体的生物特征的唯一性和“不可伪造性”使得它很适合于身份认证。生物信息本来是不保密的,所以不能象使用口令一样来使用它,否则将不能提高反而会降低系统的安全性。公钥机制(PKI)也被广泛应用于用户身份认证中,但它是基于私钥的安全性的,不可避免地存在冒用私钥的威胁。论文提出一个结合生物技术与PKI技术的认证方式的设计,具体描述了它在Secure-OSCAR中的实现。     

基于生物特征识别的门限身份认证方案

在传统生物特征身份认证系统中,针对重要目标的保护时,单一用户的身份认证方案存在用户权限过高的问题。为了解决此类问题,利用BGN半同态加密算法,结合Shamir秘密共享设计了一种基于生物特征识别的门限身份方案。主要使用在双线性对上BGN同态加密算法进行数据保护,利用第三方认证中心进行秘密分割,服务器在密文状态下对用户的身份进行认证,实现门限身份认证。通过性能分析验证了方案的安全性和高效性。     

生物特征识别及其在大型家畜个体识别中的应用研究进展*

生物特征识别具有稳定、可靠、不易伪造等优点,已广泛应用于个人身份识别中,随着对家畜疾病防疫和可追溯的需求,利用生物特征识别技术对家畜个体进行识别已成为一种趋势。综述了目前主流的几种生物特征识别技术,比较了不同技术的优缺点,分析了鼻纹识别、视网膜识别、虹膜识别三种技术在大型家畜个体识别中的应用,总结了生物特征识别技术在大型家畜个体识别中应用的趋势。     

Comparison and combination of iris matchers for reliable personal authentication

The personal identification approaches using iris images are receiving increasing attention in the biometrics literature. Several methods have been presented in the literature and those based on the phase encoding of texture information are suggested to be the most promising. However, there has not been any attempt to combine these approaches to achieve further improvement in the performance. This paper presents a comparative study of the performance from the iris authentication using Log-Gabor, Haar wavelet, DCT and FFT based features. Our experimental results suggest that the performance from the Haar wavelet and Log-Gabor filter based phase encoding is the most promising among all the four approaches considered in this work. Therefore, the combination of these two matchers is most promising, both in terms of performance and the computational complexity. Our experimental results from the all 411 users (CASIA v3) and 224 users (IITD v1) database illustrate significant improvement in the performance which is not possible with either of these approaches individually.     

Online risk-based authentication using behavioral biometrics

In digital home networks, it is expected that independent smart devices communicate and cooperate with each other, without the knowledge of the fundamental communication technology, on the basis of a distributed operating system paradigm. In such context, securing the access rights to some objects such as data, apparatus, and contents, is still a challenge. This paper introduces a risk-based authentication technique based on behavioral biometrics as solution approach to tackle this challenge. Risk-based authentication is an increasingly popular component in the security architecture deployed by many organizations to mitigate online identity fraud. Risk-based authentication uses contextual and historical information extracted from online communications to build a risk profile for the user that can be used accordingly to make authentication and authorization decisions. Existing risk-based authentication systems rely on basic web communication information such as the source IP address or the velocity of transactions performed by a specific account, or originating from a certain IP address. Such information can easily be spoofed, and as such, put in question the robustness and reliability of the proposed systems. In this paper, we propose a new online risk-based authentication system that provides more robust user identity information by combining mouse dynamics and keystroke dynamics biometrics in a multimodal framework. We propose a Bayesian network model for analyzing free keystrokes and free mouse movements involved in web sessions. Experimental evaluation of our proposed model with 24 participants yields an Equal Error Rate of 8.21 %. This is very encouraging considering that we are dealing with free text and free mouse movements, and the fact that many web sessions tend to be very short.     

A study of identical twins’ palmprints for personal verification

Automatic biometric systems based on human characteristics for personal identification have attracted great attention. Their performance highly depends on the distinctive information in the biometrics. Identical twins having the closest genetics-based relationship are expected to have maximum similarity in their biometrics. Classifying identical twins is a challenging problem for some automatic biometric systems. Palmprint has been studied for personal identification for over seven years. Most of the previous research concentrates on algorithm development. In this paper, we systemically examine palmprints from the same DNA for automatic personal identification and to uncover the genetically related palmprint features. The experimental results show that the three principal lines and some portions of weak lines are genetically related features but our palms still contain rich genetically unrelated features for classifying identical twins.