自动掌纹诊病的神经网络方法

1.引言近年来生物特征识别技术(Biometrics)的研究在身份鉴别这一应用领域取得了丰硕的成果,许多实用系统相继面市,但生物特征识别技术应用于诊断人类疾病则是一个完全崭新的应用领域,它将使生物特征技术具有更为广阔的应用前景。掌纹是人体生物特征之一,不但可用于身份鉴别,而且医学界还证明:掌纹的变化反映了人体各器官的盛衰,因此还可用来诊断人类疾病。     

生物特征识别综述*

对传统的身份鉴别手段和现代生物特征识别技术产生背景进行了综述,介绍目前典型的生物特征识别技术的原理和发展趋势,分析了实际应用中存在的优缺点,并探讨了基于个人生物特征融合的多生物特征识别技术和生物特征信息保护问题,强调了生物识别技术在身份认证领域的重要性。     

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.     

基于欧氏权距离法的多生物特征身份鉴别

通过融合不同的生物特征可以改进身份鉴别系统的验证性能。本文借鉴多传感器信息融合技术中聚类分析的思想,提出了基于欧氏权距离法的多生物特征融合的身份鉴别方法。该方法并不局限于特定的两类或多类生物特征,同时该方法克服了传统的估计方法和统计方法需要先验概率和概率密度函数的缺点,更加符合实际应用的需要。     

基于人体生物特征信息隐藏和身份认证及其应用

随着计算机网络技术的高速发展,利用网络远程获取资源和得到授权的服务越来越便捷,但是如何确保特定的资源受到保护,只对合法、授权的用户开发和使用,即如何正确地鉴别用户的身份,以确保通信网和系统数据安全,并且在当前网络环境下,研究如何保存生物特征图像的完整性,如何实现安全可靠的远程身份认证,如何确保生物特征的隐私性和秘密数据的安全性等多方面研究是当前网络资源保护研究的重要项目。本文针对人体生物特征信息隐藏和身份认证进行了深入的研究,通过人体生物的部分特征信息来实现网络身份的验证,例如通过人体指纹、人脸部形状以及虹膜等生物特征信息,通过对其研究,以保护网络资源的安全以及实现用户远程身份登录。     

关于人脸识别技术在商业银行方面的应用——基于计算机视觉

随着高科技手段的发展与应用,依靠人的身体特征来进行身份验证的生物识别技术可以代替现有的身份识别技术。人脸识别技术作为生物识别技术的一种,以其特有的稳定性、唯一性和方便性等特征,被越来越广泛地被应用在需要身份识别的领域。本文主要从计算机在生物识别技术和人脸识别技术方面的应用、人脸识别系统的组成、以及人脸识别技术在商业银行方面的应用等方面论述了人脸识别技术在身份识别方面的应用。     

基于改进ENN算法的多生物特征融合的身份验证

基于多生物特征的身份鉴别技术已受到越来越多的重视.单个生物特征有其固有的局 限性,通过融合不同的生物特征可以提高身份鉴别系统的验证性能和鲁棒性.该文融合了声纹 和指纹特征,提出了一种改进的ENN方法,并与K-NN、传统ENN方法进行了比较.改进的 ENN将认证率提高了大约2％.同时,又在不同的数据集上比较了改进的ENN方法和基于 Bayes理论的融合系统,分析并评价了两种方法的适用范围和优缺点.实验结果证明了此方法的 有效性.     

生物特征识别技术研究及应用

生物特征识别技术作为一种身份识别的手段,具有独特的优势,对信息安全具有重要意义,近年来已逐渐成为国际上的研究热点。本文介绍了生物特征的概念及多种常见生物特征识别技术,对不同的识别方法的原理、特征及性能做了较详细的分析与评价。     

USB Key身份认证技术及其在电子商务活动中的应用研究

USB Key身份认证技术是与用户名加口令、生物特征识别技术并列的三大认证技术之一,是近几年发展起来的一种方便、快捷、安全的身份认证技术。它结合了现代密码学技术、智能卡技术和USB技术的一种新型身份识别技术。本文对当前USB Key身份认证技术进行了分析,并对其的相关应用进行了探讨,希望能够对我们认识和了解USB Key身份认证技术有所帮助。     

多模态生物特征识别技术进展综述

近年来,生物特征识别已经成为一种最具潜力的身份认证技术之一.主要对多模态生物特征识别技术进行概括和总结,同时也介绍了现存若干用于身份识别和验证的多模态生物特征识别系统.经调查研究显示,多模态生物特征识别技术由于在身份认证和识别过程中考虑了个体的多种生理或行为特征,因而表现出了较单生物特征更高的可靠性和安全性,并已成为生物特征识别技术未来发展的趋势之一.     

多生物特征识别

生物特征的识别技术是一门利用人类特有的个体特征来验证个人身份的科学，它与 传统的基于口令和个人身份号码的识别方法相比更加可靠．本文先对各种不同生物特征识别 技术作了简要介绍，然后，介绍了多生物特征识别技术及其工作原理和方法，对生物特征识 别技术的应用前景和发展方向进行了分析．     

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.

     

指纹识别技术的研究

由于人体指纹具有唯一性和不变性,使得指纹识别与传统身份识别的方法相比具有更高的安全性和易用性.本文阐述了生物特征识别的发展历史、应用背景,并着重介绍指纹识别系统的工作流程、分类及研究现状.     

基于个人特征的身份认证技术的发展与应用

介绍了认证技术,总结了基于个人特征的身份认证技术的发展,提出了基于个人特征的身份认证技术在公钥管理和计算机安全管理中的应用方法。     

Computational Intelligence-Based Biometric Technologies

Computational intelligence (CI) technologies are robust, can be successfully applied to complex problems, are efficiently adaptive, and usually have a parallel computational architecture. For those reasons they have been proved to be effective and efficient in bio-metric feature extraction and biometric matching tasks, sometimes used in combination with traditional methods. In this article, we briefly survey two kinds of major applications of CI in biometric technologies, CI-based feature extraction and CI-based biometric matching. Varieties of evolutionary computation and neural networks techniques have been successfully applied to biometric data representation and dimensionality reduction. CI-based methods, including neural network and fuzzy technologies, have also been extensively investigated for biometric matching. CI-based biometric technologies are powerful when used in the representation and recognition of incomplete biometric data, discriminative feature extraction, biometric matching, and online template updating, and promise to have an important role in the future development of biometric technologies     

WINDOWS指纹登录系统的设计与实现

自动指纹识别作为一种较为成熟的生物特征识别技术,相对于传统的“ID+密码”的身份认证方式而言,具有安全方便的优点,近年来得到研究人员越来越多的关注。针对传统WINDOWSNT/2000登录方式安全性不足、操作不方便的问题,该文提出了指纹识别技术与WINDOWS身份验证相结合的解决方案,开发了基于指纹识别的WINDOWS登录系统,以增强现有系统的安全性,同时免去用户输入和记忆密码的负担。     

构建基于Intel PXA255的指纹识别系统

指纹识别是身份验证中一种重要的生物识别技术.指纹具有唯一性、不变性、易于获取等特性,这使得指纹识别成为生物鉴定学中最为成熟的方式.嵌入式指纹识别系统集成了模式识别,图像处理,智能卡,数据库等技术,适用于多种应用场合,应用前景广阔.下面讨论基于Intel XScale PXA255处理器和Windows CE.net嵌入式操作系统构建自动指纹识别系统.     

Towards a multi-source fusion approach for eye movement-driven recognition

This paper presents a research for the use of multi-source information fusion in the field of eye movement biometrics. In the current state-of-the-art, there are different techniques developed to extract the physical and the behavioral biometric characteristics of the eye movements. In this work, we explore the effects from the multi-source fusion of the heterogeneous information extracted by different biometric algorithms under the presence of diverse visual stimuli. We propose a two-stage fusion approach with the employment of stimulus-specific and algorithm-specific weights for fusing the information from different matchers based on their identification efficacy. The experimental evaluation performed on a large database of 320 subjects reveals a considerable improvement in biometric recognition accuracy, with minimal equal error rate (EER) of 5.8%, and best case Rank-1 identification rate (Rank-1 IR) of 88.6%. It should be also emphasized that although the concept of multi-stimulus fusion is currently evaluated specifically for the eye movement biometrics, it can be adopted by other biometric modalities too, in cases when an exogenous stimulus affects the extraction of the biometric features.     

Hiding biometric data

With the wide spread utilization of biometric identification systems, establishing the authenticity of biometric data itself has emerged as an important research issue. The fact that biometric data is not replaceable and is not secret, combined with the existence of several types of attacks that are possible in a biometric system, make the issue of security/integrity of biometric data extremely critical. We introduce two applications of an amplitude modulation-based watermarking method, in which we hide a user's biometric data in a variety of images. This method has the ability to increase the security of both the hidden biometric data (e.g., eigen-face coefficients) and host images (e.g., fingerprints). Image adaptive data embedding methods used in our scheme lead to low visibility of the embedded signal. Feature analysis of host images guarantees high verification accuracy on watermarked (e.g., fingerprint) images.     

Authentication by Biometric Verification

Biometric systems encompass the development of capture devices to acquire biometric signals, software algorithms for effective identification, and databases that store biometric data for comparison.