Bayesian adaptation for user-dependent multimodal biometric authentication

A novel score-level fusion strategy based on Bayesian adaptation for user-dependent multimodal biometric authentication is presented. In the proposed method, the fusion function is adapted for each user based on prior information extracted from a pool of users. Experimental results are reported using on-line signature and fingerprint verification subsystems on the MCYT real bimodal database. The proposed scheme outperforms both user-independent and user-dependent standard approaches. As compared to non-adapted user-dependent fusion, relative improvements of 80% and 55% are obtained for small and large training set sizes, respectively.     

Discriminative multimodal biometric authentication based on quality measures

A novel score-level fusion strategy based on quality measures for multimodal biometric authentication is presented. In the proposed method, the fusion function is adapted every time an authentication claim is performed based on the estimated quality of the sensed biometric signals at this time. Experimental results combining written signatures and quality-labelled fingerprints are reported. The proposed scheme is shown to outperform significantly the fusion approach without considering quality signals. In particular, a relative improvement of approximately 20% is obtained on the publicly available MCYT bimodal database.     

Adapted user-dependent multimodal biometric authentication exploiting general information

A novel adapted strategy for combining general and user-dependent knowledge at the decision level in multimodal biometric authentication is presented. User-independent, user-dependent, and adapted fusion and decision schemes are compared by using a bimodal system based on fingerprint and written signature. The adapted approach is shown to outperform the other strategies considered in this paper. Exploiting available information for training the fusion function is also shown to be better than using existing information for post-fusion trained decisions.     

Biosec baseline corpus: A multimodal biometric database

The baseline corpus of a new multimodal database, acquired in the framework of the FP6 EU BioSec Integrated Project, is presented. The corpus consists of fingerprint images acquired with three different sensors, frontal face images from a webcam, iris images from an iris sensor, and voice utterances acquired both with a close-talk headset and a distant webcam microphone. The BioSec baseline corpus includes real multimodal data from 200 individuals in two acquisition sessions. In this contribution, the acquisition setup and protocol are outlined, and the contents of the corpus—including data and population statistics—are described. The database will be publicly available for research purposes by mid-2006.     

Usability evaluation of voiceprint authentication in automated telephone banking: Sentences versus digits

This paper describes an experiment to investigate the usability of voiceprints for customer authentication in automated telephone banking. The usability of voiceprint authentication using digits (random strings and telephone numbers) and sentences (branded and unbranded) are compared in a controlled experiment with 204 telephone banking customers. Results indicate high levels of usability and customer acceptance for voiceprint authentication in telephone banking. Customers find voiceprint authentication based on digits more usable than that based on sentences, and a majority of participants would prefer to use digits.     

网络认证技术新发展

文章分析了身份认证的必要性和发展现况,详细介绍了常见实体认证手段和基于密码学认证协议。随着移动通信的迅猛发展,身份认证和认证协议都出现许多研究热点。在HMAC算法的基础上还提出了一种改进认证协议,可以有效防止消息的重传。     

WLAN环境下EAP-TLS认证机制的分析与实现

认证是计算机网络安全中的核心内容,是实现计算机网络安全的基础,在无线网络安全中同样占有非常重要的地位。在研究了无线局域网(WLAN)的认证机制基础上,其中扩展认证协议-传输层安全(EAP-TLS)是目前安全性能较高的认证方式,在实际网络平台中对其进行分析与实现。     

A secure authentication scheme for Internet of Things

Security is one of the major issues in Internet of Things (IoT) research. The rapid growth in the number of IoT devices, the heterogeneity and complexity of these objects and their networks have made authentication a challenging task. Other constraints such as limited computational ability and power, and small storage of some embedded devices make implementation of complex cryptographic algorithms difficult. So far there has been no established industrial standard to address this problem.Recently, Kalra and Sood, and subsequently Chang et al. attempted to solve the authentication problem by proposing key agreement schemes for IoT devices. However, the security of their schemes were unproven. In this paper we demonstrate that these schemes are insecure. We extend upon their work to present a scheme that enables embedded devices to communicate securely with a server on an IoT network. We prove the security of this scheme using formal methods and demonstrate this under the intractability of some well-defined hard problems. We also discuss some practical aspects related to the implementation of the scheme.     

A review of biometric technology along with trends and prospects

Identity management through biometrics offer potential advantages over knowledge and possession based methods. A wide variety of biometric modalities have been tested so far but several factors paralyze the accuracy of mono-modal biometric systems. Usually, the analysis of multiple modalities offers better accuracy. An extensive review of biometric technology is presented here. Besides the mono-modal systems, the article also discusses multi-modal biometric systems along with their architecture and information fusion levels. The paper along with the exemplary evidences highlights the potential for biometric technology, market value and prospects.     

Improvement of the RFID authentication scheme based on quadratic residues

RFID, with its capability of remote automatic identification, is taking the place of barcodes and becoming the new generation of electronic tags. However, information transmitted through the air is vulnerable to eavesdropping, interception, or modification due to its radio transmission nature; the prevalence of RFID has greatly increased security and privacy concerns. In 2008, Chen et al. proposed an RFID authentication scheme which can enhance security and privacy by using hash functions and quadratic residues. However, their scheme was found to be vulnerable to impersonation attacks. This study further demonstrates that their scheme does not provide location privacy and suffers from replay attacks. An improved scheme is also proposed which can prevent possible attacks and be applied in environments requiring a high level of security.     

基于FPS110的智能指纹识别系统设计

本文设计了以S3C2410处理器为核心,基于指纹传感器FPS110的智能指纹识别系统,电路规模小,易于应用。并通过应用圆形Gabor滤波算法实现了对图像的预处理和对比。系统的指纹识别率较高,具有较好的使用价值。     

Management of access through biometric control: A case study based on automatic signature verification

The idea of the information society is pervasive and varied and, in this context, universal access is itself a multi-faceted concept. However, the notion of universality presupposes an analysis and understanding of what both unifies and discriminates among different individual members of a community of technology users. This paper addresses these ideas and, in particular, seeks to illustrate some techniques which can support such an analysis in a variety of task domains. Of special interest here is a specific case study which examines the use of biometric processing as a means of managing access in the broadest sense. It is argued that not only is the field of biometric measurement one where understanding similarities and differences is the essence of what is required, but also that this offers the opportunity to establish and explore a variety of practical techniques of very wide significance in the context of universal access. Published online: 18 May 2001     

Coding behavior of authentication code on the internet

With the rapid growth of Internet services, virtual world has witnessed an increasingly large number of online users who have a variety of needs such as accessing various websites to gather information, easing business transactions, and sharing updates. As a result, information security has become a major concern among online users, and the verification of access codes is now the main practice used to keep information systems safe. However, some issues arise as the result of coding and managing behavior, and this research seeks to address these issues. After following the Focus Group method and interviewing 13 college students, this research finds that forgetting the access code is one of the biggest challenges to most online users simply because of the longer duration and the time when the users have a need to access the websites again, their memory will eclipse. In addition, online users usually develop self-constructed rules to cope with elusive code. These rules include: creating some sets of code that may not be meaningful to outsiders; taking different degrees of complex measures to register authentication codes, dependent upon the importance of the websites to the online users; writing the authentication codes on a scratchpad and sticking it on the computer screen; and keeping the codes in a notebook or computer file. The above practices nevertheless run the risk of being usurped by hackers, and it is found that hacking frequently takes place among closest friends, as they are quite familiar with the coding behavior of the victims. While assisting coding management does not help in this regard, as it is generally too expensive, online users troubled by the forgetting of access codes often end up with re-applying for a new set of authentication codes after unsuccessfully trying to login. All these self-constructed rules, nevertheless, constitute threat to information security. The research, in conclusion, calls for an education campaign to promote healthy coding behavior and effective coding management. The obtained findings provide valuable references for both academicians and practitioners to understand the online users’ coding behaviors and to effectively manage them accordingly to improve the resulting information security.     

身份认证威胁与对抗措施分析

本文讨论了身份认证面对的威胁,建立了相应的安全威胁模型,有针对性的研究各种身份认证威胁的对抗措施,并提供相应的技术支持。对身份认证面对的威胁的讨论中,主要介绍了身份认证的基本途径并提出了威胁模型;对身份认证威胁的对抗措施的讨论中,主要介绍了人为干预措施以及STRIDE威胁对抗措施。     

A transverse local feedback linearization approach to human head movement control

In the mid-nineteenth century, Donders had proposed that for every human head rotating away from the primary pointing direction, the rotational vectors in the direction of the corresponding axes of rotation, is restricted to lie on a surface. Donders'' intuition was that under such a restriction, the head orientation would be a function of its pointing direction. In this paper, we revisit Donders'' Law and show that indeed the proposed intuition is true for a restricted class of head-orientations satisfying a class of quadratic Donders'' surfaces, if the head points to a suitable neighborhood of the frontal pointing direction. Moreover, on a suitably chosen subspace of the 3D rotation group ${rm SO}(3)$, we describe a head movement dynamical system with input control signals that are the three external torques on the head provided by muscles. Three output signals are also suitably chosen as follows. Two of the output signals are coordinates of the frontal pointing direction. The third signal measures deviation of the state vector from the Donders'' surface. We claim that the square system is locally feedback linearizable on the subspace chosen, and the linear dynamics is decomposed into parts, transverse and tangential to the Donders'' surface. We demonstrate our approach by synthesizing a tracking and path-following controller. Additionally, for different choices of the Donders'' surface parameters, head gaits are visualized by simulating different movement patterns of the head-top vector, as the head-pointing vector rotates around a circle.     

Mining a new biometrics to improve the accuracy of keystroke dynamics-based authentication system on free-text

Related works for applying keystroke dynamics (KD) on free text identification indicated that applying KD can improve the accuracy of personal authentication on free text. As the result, this paper proposes a new biometrics, i.e., the keystroke clusters map (KC-Map), by clustering users’ keystrokes in order to effectively enhance the accuracy of personal authentication in free text. Since KC-Map is conducted via clustering, it is not suitable for traditional classifiers. In order to tackle this problem, the paper further proposes a keystroke clusters map similarity classifier (KCMS classifier). Experimental results positively show that the proposed KC-Map and KCMS classifier can efficiently improve the accuracy of personal authentication on free text with up to 1.27 times. In addition, one of the huge disadvantages on the current approaches in free text identification is that users are generally required to be trained for several months. Longer training time makes free text identification more impractical. Another motivation of this paper is to explore whether it is possible to shorten the training time into an acceptable range. Experimental results show that, to achieve relatively fair identification accuracy, users only need to carry out about 20 min for training.     

Authentication of Individuals using Hand Geometry Biometrics: A Neural Network Approach

Biometric based systems for individual authentication are increasingly becoming indispensable for protecting life and property. They provide ways for uniquely and reliably authenticating people, and are difficult to counterfeit. Biometric based authenticity systems are currently used in governmental, commercial and public sectors. However, these systems can be expensive to put in place and often impose physical constraint to the users. This paper introduces an inexpensive, powerful and easy to use hand geometry based biometric person authentication system using neural networks. The proposed approach followed to construct this system consists of an acquisition device, a pre-processing stage, and a neural network based classifier. One of the novelties of this work comprises on the introduction of hand geometry’s related, position independent, feature extraction and identification which can be useful in problems related to image processing and pattern recognition. Another novelty of this research comprises on the use of error correction codes to enhance the level of performance of the neural network model. A dataset made of scanned images of the right hand of fifty different people was created for this study. Identification rates and Detection Cost Function (DCF) values obtained with the system were evaluated. Several strategies for coding the outputs of the neural networks were studied. Experimental results show that, when using Error Correction Output Codes (ECOC), up to 100% identification rates and 0% DCF can be obtained. For comparison purposes, results are also given for the Support Vector Machine method.     

Improvement of the secure dynamic ID based remote user authentication scheme for multi-server environment

Recently, Liao and Wang proposed a secure dynamic ID based remote user authentication scheme for multi-server environment, and claimed that their scheme was intended to provide mutual authentication, two-factor security, replay attack, server spoofing attack, insider and stolen verifier attack, forward secrecy and user anonymity. In this paper, we show that Liao and Wang's scheme is still vulnerable to insider's attack, masquerade attack, server spoofing attack, registration center spoofing attack and is not reparable. Furthermore, it fails to provide mutual authentication. To remedy these flaws, this paper proposes an efficient improvement over Liao–Wang's scheme with more security. The computation cost, security, and efficiency of the improved scheme are well suited to the practical applications environment.     

Evaluation of head and neck motion with the hemispherical shell method

This paper presents the development of a simple method for the measurement of head motion for patients with neck injuries. The patients with neck injuries pose unique problems and the existing methods mostly using goniometers are not suitable for their evaluation in a clinical setting. The presented method involves the use of a hemispherical shell mounted with the help of a frame over the head of the patient. Two light sources are mounted on the patient's head and the readings are taken from circular scales marked on the outer shell surface. Equations are developed to convert these readings into the ranges of head motion. The results obtained with the presented method for normal adults are compared with the results from the previous methods. The data for the patients with neck injuries will be useful in the individualized design of instruments such as headstick operated keyboards, computers or keyboard-like devices.

Relevance to industry

For the industrial employment of patients with neck injuries, an accurate evaluation of their abilities is important, particularly when job modifications are needed so that they can be viable employees in industry. The head motion obtained with this new method for patients with neck injuries will be useful in the individualized design of instruments such as headstick operated keyboards, computer interfaces, communication devices or keyboard-like devices. The proposed method is simple, inexpensive, reasonably accurate and can be used in a clinical setting.     

A telebiometric system mechanism model and biometric network protocol for the security of networked manufacturing

Networked manufacturing changes conventional enterprise activities. With a networked manufacturing system, enterprises are able to perform a range of activities, such as product planning, design, production, and marketing, in collaboration with international partners, regardless of geographical location. However, strict security measures are required, as the authentication and information transfers for networked manufacturing are conducted over a network. With the development of biometric technology, more and more enterprises are using the unique biometric data of individuals to verify the identity of users, in order to restrict and provide access to technology research centers or factory facilities. This paper analyzes the vulnerabilities of the biometric system used for access control and the authentication of access to confidential information in the networked manufacturing system. In addition, the biometric systems that can be built in an open network environment are classified into 9 general models, and a biometric network protocol is suggested that is secure and compatible with international standards.