Applied Numerical Analysis. By C.F. Gerald. Pp. xii, 340. £3·60. 1970. (Addison-Wesley.)

Biometric recognition offers a reliable solution to the problem of user authentication in identity management systems. With the widespread deployment of biometric systems in various applications, there are increasing concerns about the security and privacy of biometric technology. Public acceptance of biometrics technology will depend on the ability of system designers to demonstrate that these systems are robust, have low error rates, and are tamper proof. We present a high-level categorization of the various vulnerabilities of a biometric system and discuss countermeasures that have been proposed to address these vulnerabilities. In particular, we focus on biometric template security which is an important issue because, unlike passwords and tokens, compromised biometric templates cannot be revoked and reissued. Protecting the template is a challenging task due to intrauser variability in the acquired biometric traits. We present an overview of various biometric template protection schemes and discuss their advantages and limitations in terms of security, revocability, and impact on matching accuracy. A template protection scheme with provable security and acceptable recognition performance has thus far remained elusive. Development of such a scheme is crucial as biometric systems are beginning to proliferate into the core physical and information infrastructure of our society.

/pdf/biometric-template-security-3nxd1k841h.pdf

Biometric template security

In recent years, along with the extraordinary diffusion of the Internet and a growing need for personal verification in many daily applications, automatic signature verification is being considered with renewed interest. This paper presents the state of the art in automatic signature verification. It addresses the most valuable results obtained so far and highlights the most profitable directions of research to date. It includes a comprehensive bibliography of more than 300 selected references as an aid for researchers working in the field.

/pdf/automatic-signature-verification-the-state-of-the-art-68njryqnhw.pdf

Automatic Signature Verification: The State of the Art

At some point in the future, how far out we do not exactly know, wireless access to the Internet will outstrip all other forms of access bringing the freedom of mobility to the way we access the we...

ACM SIGCOMM computer communication review

Keystroke dynamics-the analysis of typing rhythms to discriminate among users-has been proposed for detecting impostors (i.e., both insiders and external attackers). Since many anomaly-detection algorithms have been proposed for this task, it is natural to ask which are the top performers (e.g., to identify promising research directions). Unfortunately, we cannot conduct a sound comparison of detectors using the results in the literature because evaluation conditions are inconsistent across studies. Our objective is to collect a keystroke-dynamics data set, to develop a repeatable evaluation procedure, and to measure the performance of a range of detectors so that the results can be compared soundly. We collected data from 51 subjects typing 400 passwords each, and we implemented and evaluated 14 detectors from the keystroke-dynamics and pattern-recognition literature. The three top-performing detectors achieve equal-error rates between 9.6% and 10.2%. The results-along with the shared data and evaluation methodology-constitute a benchmark for comparing detectors and measuring progress.

/pdf/comparing-anomaly-detection-algorithms-for-keystroke-32ay1s1r76.pdf

Comparing anomaly-detection algorithms for keystroke dynamics

This paper uses a static keystroke dynamics in user authentication. The inputs are the key down and up times and the key ASCII codes captured while the user is typing a string. Four features (key code, two keystroke latencies, and key duration) were analyzed and seven experiments were performed combining these features. The results of the experiments were evaluated with three types of user: the legitimate, the impostor and the observer impostor users. The best results were achieved utilizing all features, obtaining a false rejection rate of 1.45% and a false acceptance rate of 1.89%. This approach can be used to improve the usual login-password authentication when the password is no more a secret. This paper innovates using four features to authenticate users.

User authentication through typing biometrics features

In this paper, we address the security of multimodal biometric systems when one of the modes is successfully spoofed. We propose two novel fusion schemes that can increase the security of multimodal biometric systems. The first is an extension of the likelihood ratio based fusion scheme and the other uses fuzzy logic. Besides the matching score and sample quality score, our proposed fusion schemes also take into account the intrinsic security of each biometric system being fused. Experimental results have shown that the proposed methods are more robust against spoof attacks when compared with traditional fusion methods.

https://www.cedar.buffalo.edu/~govind/papers/rlg09.pdf

Robustness of multimodal biometric fusion methods against spoof attacks

This paper presents a new approach for biometric authentication based on keystroke dynamics through numerical keyboards. The input signal is generated in real time when the user enters with target string. Five features were extracted from this input signal (ASCII key code and four keystroke latencies) and four experiments using samples for genuine and impostor users were performed using two pattern classification technics. The best results were achieved by the HMM (EER=3.6%). This new approach brings security improvements to the process of user authentication, as well as it allows to include biometric authentication in mobile devices, such as cell phones.

/pdf/biometric-access-control-through-numerical-keyboards-based-4j6e6fy4bw.pdf

Biometric access control through numerical keyboards based on keystroke dynamics

This paper proposes a new hybrid handwritten signature verification system where the on-line reference data acquired through a digitizing tablet serves as the basis for the segmentation process of the corresponding scanned off-line data. Local foci of attention over the image are determined through a self-adjustable learning process in order to pinpoint the feature extraction process. Both local and global primitives are processed and the decision about the authenticity of the specimen is defined through similarity measurements. The global performance of the system is measured using two different classifiers.

A hybrid on/off line handwritten signature verification system

Iris segmental ion is one of the crucial operations involved in iris recognition. Accurate iris segmentation is fundamental for the success and precision of the subsequent feature extraction and recognition, and consequently the high performance level of the iris recognition system. Most iris segmentation approaches proposed in the literature require highly complex-exhaustive search and learning of many modeling parameters and characteristics. which prevents their effective real-time applications and makes the system highly sensitive to noise. This paper presents a fast and efficient iris segmental ion methodology to address relatively simple solutions to these problems. Three major procedures involved in the proposed iris segmentation approach, namely pupil detection, limbic boundary localization. and eyelid and eyelash detection, were carefully designed in order to avoid unnecessary and redundant image processing, and most importantly, to preserve the integrity of iris texture information. The proposed iris segmentation algorithm has the following particular properties and advantages: (a) avoidance of complex geometric and mathematical modcling: (b) no need of a training phase for algorithm design and implementation: (c) guaranteeing real-time iris segmentation even for iris images with severe occlusions: (d) high accuracy in iris segmentation and therefore Ion segmentation error rate. Expcrimcntal results. reported in this piper, demonstrate that the proposed iris segmentation algorithm outperforms some well-known methods in both accuracy and processing speed. As a consequence, the iris recognition system that incorporates the proposed iris segmentation algorithm is capable of offering recognition performances comparable with those reported by other state-of-the-art methods.

Lee Luan Ling

Papers

User authentication through typing biometrics features

Robustness of multimodal biometric fusion methods against spoof attacks

Biometric access control through numerical keyboards based on keystroke dynamics

A hybrid on/off line handwritten signature verification system

Fast and Efficient Iris Image Segmentation