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。     

生物特征信息处理开发包BITK及其应用平台

由于人类固有的生物特征能用来进行可靠的身份认证和识别,近10年来生物特征识别已经成为研究热点.为了对生物特征识别研究提供软件支持,设计研发了生物特征信息处理开发包 (Biometric Information Processing Toolkit,BITK).BITK是一个C 软件开发包.它以非线性数据流模型来组织整体计算流程,提供了一个可扩展、可重用的框架来整合生物特征识别领域的算法和数据结构.BITK还设计了一个精干的可视化框架以及一个管理各种生物特征采集仪的一致性框架.此外,在BITK基础上研发了生物特征信息处理平台 (BITK-based Application Platform,BITKAPP).该平台通过灵活的plug-in架构和友好的用户界面,充分发挥BITK的功能,并降低了BITK的使用门槛.在实际应用中,BITK和BITKAPP向研究人员提供了一套高效率的研究、实验及开发手段,并且作为支撑平台完成了第一届生物特征识别竞赛(the 1st Biometric Verification Competition)的多模态数据采集任务.     

多模态生物特征信息安全防护体系研究

在新的计算能力和深度学习技术推动下,人工智能、大数据发展进入了繁荣期,导致多模态生物特征信息迅猛增加与应用.由于多模态生物识别具有自然性和多场景应用性,特征信息的采集、识别、分析不仅涉及个人隐私和人格尊严,还主动或被动暴露在现实环境中,高校面临着巨大的信息安全保护需求和风险挑战.通过对高校多模态生物特征信息安全问题及现...     

基于模糊循环随机映射的人脸生物特征加密算法

随着生物特征识别技术的广泛应用,其安全性方面的缺陷也逐渐暴露出来。密码技术与生物特征识别技术相结合的生物特征加密技术,就是为了弥补生物特征识别在安全方面的不足而产生的。在研究已有人脸生物特征识别技术的基础上,提出一种兼具安全性及容错能力的人脸生物特征加密算法:模糊循环随机映射(Fuzzy Cyclic Random Mapping,FCRM)。在每次循环中,加密模型使用前一次循环的密钥作为随机种子生成映射矩阵,对用户的人脸特征进行映射,形成一个循环的随机映射过程。加密过程中,还使用了容错技术来减少合法用户人脸图像和特征的随机噪声对识别率的影响,而循环的映射过程能够在不减少认证准确率的前提下,阻止非法用户通过认证。     

指纹为IT上锁

在计算机系统中,保护数据和识别用户的传统办法是字 符密码,但越来越多的密码给用户造成了记忆上的负担,而 且容易被破解。微软创始人Bill Gates在2004年2月的 RSA安全会议上表示:“无疑,在以后的日子里用户将更少 地依赖于密码的保护。目前用户必须记住在不同场合下的 许多不同密码,而这一做法显然有悖于安全的初 衷。”微软由此也跟随业界趋势,积极倡导以 生物认证技术(Biometric)来替代或补 充传统的密码技术。     

生物特征识别技术走向

当前,人们谈论最多的是个人隐私的保护问题,无论是日常生活中的门禁系统、ATM提款系统,还是工作中可能遇到的计算机中数据的存取以及网络交易中的身份确认。传统的安全保护方式不外乎密码、个人识别码(PIN)、磁卡或钥匙,但这些方法只能提供有限的保障,而且它们经常会被非法盗用或滥用,造成个人隐私及财务的损失。随着技术的发展,近年来生物特征识别技术以其特有的稳定性、惟一性和方便性,被越来越广泛地应用在安全、认证等身份鉴别领域。     

基于生物特性下识别技术的应用研究

生物识别技术是目前传感研究中的一项重要技术,利用生物固有的特性,如脸型、身体轮廓、虹膜、步态特征等进行身份验证,生物识别是基于原有的传感设备之上采用光学采集生物特征数据,通过计算机特定的算法对其进行编码,生物特性识别技术的发展与应用,提高了当前较为复杂的交通与金融系统的安全性与工作效益.     

手指静脉采集技术综述

近年来,生物识别技术在基础理论、算法模型、创新应用、软硬件支撑等方面不断取得突破.文章对手指静脉采集技术进行了探讨,包括使用近红外激光的接触式和非接触式手指静脉采集,以及使用重复线跟踪方法对手指静脉图像的提取等.手指静脉作为内部固有生物特征,与其他生物特征(例如指纹,人脸,声纹等)相比,更能满足高安全场所的应用需求,可以为任何身份验证提供更安全和准确的生物识别信息.     

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.     

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.     

模糊逻辑在人脸特征保护算法中的应用

随着人脸识别在门禁、视频监控等公共安全领域中的应用日益广泛,人脸特征数据的安全性和隐私性问题成为备受关注的焦点。近年来出现了许多关于生物特征及人脸特征的安全保护算法,这些算法大都是将生物特征数据转变为二值的串,再进行保护。针对已有的保护算法中将实值的人脸特征转换为二值的串,从而导致信息丢失的不足,应用模糊逻辑对人脸模板数据的类内差异进行建模,从而提高人脸识别系统的性能。给出了算法在CMU PIE的光照子集、CMU PIE带光照和姿势的子集和ORL人脸数据库中的实验结果。实验表明,该算法能够进一步提高已有安全保护算法的识别率。     

基于比特流的虹膜特征数据的隐藏算法

对生物特征数据的攻击是生物特征识别自身安全的主要威胁。为了提高虹膜特征数据的安全性,根据现有主要的虹膜识别方法中特征模板的数据特性和基于汉明距的比对方法,提出一种基于比特流的将虹膜特征模板数据嵌入人脸图像的数据隐藏算法。实验结果表明,该算法具有较强的隐蔽性,隐藏算法本身误码率为零,计算效率高,不会影响虹膜识别技术本身的性能,能够有效保护特征模板数据,增强虹膜识别系统自身的安全性。     

Cancelable features using log-Gabor filters for biometric authentication

Wide spread use of biometric based authentication requires security of biometric data against identity thefts. Cancelable biometrics is a recent approach to address the concerns regarding privacy of biometric data, public confidence, and acceptance of biometric systems. This work proposes a template protection approach which generates revocable binary features from phase and magnitude patterns of log-Gabor filters. Multi-level transformations are applied at signal and feature level to distort the biometric data using user specific tokenized variables which are observed to provide better performance and security against information leakage under correlation attacks. A thorough analysis is performed to study the performance, non-invertibility, and changeability of the proposed approach under stolen token scenario on multiple biometric modalities. It is revealed that generated templates are non-invertible, easy to revoke, and also deliver good performance.     

A practical guide to biometric security technology

As organizations search for more secure authentication methods for user access, e-commerce. and other security applications, biometrics is gaining increasing attention. But should your company use biometrics? And, if so, which ones should you use and how do you choose them? There is no one best biometric technology. Different applications require different biometrics. To select the right biometric for your situation, you will need to navigate through some complex vendor products and keep an eye on future developments in technology and standards. Your options have never been more diverse. After years of research and development, vendors now have several products to offer. Some are relatively immature, having only recently become commercially available, but even these can substantially improve your company's information security posture. We briefly describe some emerging biometric technologies to help guide your decision making     

Biometric template protection using cancelable biometrics and visual cryptography techniques

Wide spread use of biometric based authentication implies the need to secure biometric reference data. Various template protection schemes have been introduced to prevent biometric forgery and identity thefts. Cancelable biometrics and visual cryptography are two recent technologies introduced to address the concerns regarding privacy of biometric data, and to improve public confidence and acceptance of biometric systems. Cancelable biometrics is an important technique that allows generation of revocable biometric templates. As the number of biometric instances are limited and once compromised they are lost forever. Cancelable biometrics allows templates to be cancelled and revoked like passwords innumerable times. Recently, various approaches that utilize visual cryptography to secure the stored template and impart privacy to the central databases have been introduced. This work attempts to summarize the existing approaches in literature making use of these two technologies to protect biometric templates.     

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.

     

一种单因子的可撤销生物特征认证方法

将令牌化随机数作为外部因子的双因子可撤销生物特征认证方法存在令牌泄露、丢失等安全威胁. 本文提出了一种生物特征作为唯一输入的解决方法, 即单因子的可撤销生物特征认证方法. 首先, 利用扩展的特征向量, 通过预定义的滑动窗口和哈希函数随机化生成二进制种子; 然后替换不同的辅助数据来生成可撤销模板; 最后, 由查询生物特征向量对辅助数据进行解码, 提高了性能和安全性. 在指纹数据库FVC2002和FVC2004的实验结果表明, 该方法不仅满足可撤销生物特征识别的4个设计标准, 同时防御了3种安全攻击.     

Graphics and security: exploring visual biometrics

Biometrics technology has come a long way from simpler forms of systems security. But are biometrics-based systems more secure or do they simply require crackers to become more proficient at breaking into systems? To recognize your fingerprint requires that a template of your fingerprint actually be present in the system that verifies your access. If you want to pass as somebody else, presumably you'd have to either have that person's finger with you or you'd need to change the verifying template residing in the system that verifies your print. Cracking into a system and replacing a legitimate print with your own isn't easy to do unless the system's security is poor. While biometric proponents stress the strength of their proprietary technologies or biometrics in general, no system is ever completely secure. Contrary to what many biometric proponents would have us believe-that biometric security outclasses traditional forms of security-all biometric systems are, after all, another form of computer security with its own set of strengths and weaknesses. Biometrics effectively trade some amount of privacy and cost effectiveness for ultimate convenience-and these systems are certainly no less secure than standard password systems. Password systems are cheap. Complex biometric scanning equipment is usually expensive. But biometrics seems to be where the industry is headed.     

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.     

Privacy preserving security using biometrics in cloud computing

Cloud computing and the efficient storage provide new paradigms and approaches designed at efficiently utilization of resources through computation and many alternatives to guarantee the privacy preservation of individual user. It also ensures the integrity of stored cloud data, and processing of stored data in the various data centers. However, to provide better protection and management of sensitive information (data) are big challenge to maintain the confidentiality and integrity of data in the cloud computation. Thus, there is an urgent need for storing and processing the data in the cloud environment without any information leakage. The sensitive data require the storing and processing mechanism and techniques to assurance the privacy preservation of individual user, to maintain the data integrity, and preserve confidentiality. Face recognition has recently achieved advancements in the unobtrusive recognition of individuals to maintain the privacy-preservation in the cloud computing. This paper emphasizes on cloud security and privacy issues and provides the solution using biometric face recognition. We propose a biometrics face recognition approach for security and privacy preservation of cloud users during their access to cloud resources. The proposed approach has three steps: (1) acquisition of face images (2) preprocessing and extraction of facial feature (3) recognition of individual using encrypted biometric feature. The experimental results establish that our proposed recognition approach can ensure the privacy and security of biometrics data.