Showing papers on "Biometrics published in 2005"

Large-scale evaluation of multimodal biometric authentication using state-of-the-art systems

Abstract: We examine the performance of multimodal biometric authentication systems using state-of-the-art commercial off-the-shelf (COTS) fingerprint and face biometric systems on a population approaching 1,000 individuals. The majority of prior studies of multimodal biometrics have been limited to relatively low accuracy non-COTS systems and populations of a few hundred users. Our work is the first to demonstrate that multimodal fingerprint and face biometric systems can achieve significant accuracy gains over either biometric alone, even when using highly accurate COTS systems on a relatively large-scale population. In addition to examining well-known multimodal methods, we introduce new methods of normalization and fusion that further improve the accuracy.

An evaluation of multimodal 2D+3D face biometrics

Abstract: We report on the largest experimental study to date in multimodal 2D+3D face recognition, involving 198 persons in the gallery and either 198 or 670 time-lapse probe images. PCA-based methods are used separately for each modality and match scores in the separate face spaces are combined for multimodal recognition. Major conclusions are: 1) 2D and 3D have similar recognition performance when considered individually, 2) combining 2D and 3D results using a simple weighting scheme outperforms either 2D or 3D alone, 3) combining results from two or more 2D images using a similar weighting scheme also outperforms a single 2D image, and 4) combined 2D+3D outperforms the multi-image 2D result. This is the first (so far, only) work to present such an experimental control to substantiate multimodal performance improvement.

Method for identity verification

Abstract: The method for identity verification employs biometric technology. Positioned at the center of the system is a stylus with any of a number of biometric properties or their combination or with one or more metric sensors, while the customer uses the stylus to sign his/her name, or even for writing anything. The identity verification system is used at point-of-sale terminals, in various closed environments, to access a computer network, in applications involving pen-based computers and smart-pens, and for e-commerce. When fingerprint sensors are used, the sensors are positioned in the stylus grip, one sensor for the index finger, and a second sensor for the thumb. In one variation, one-to-one biometric matching is used. Each participant carries on his/her person a device that includes an encrypted biometric for reference purposes to gain access Into the system. Processing is simplified since the system need only make a “MATCH” or “NO MATCH” decision. In a second variation that is particularly useful in closed environments, one-to-many biometric matching is used. During each event access request, the community of reference prints is searched for a match with the applicant. Each member of the community need carry nothing on his/her person to participate in the system. In either variation, the stylus is either attached to each site or is portable, one such stylus being carried by each participant.

Fuzzy vault for fingerprints

Abstract: Biometrics-based user authentication has several advantages over traditional password-based systems for standalone authentication applications, such as secure cellular phone access. This is also true for new authentication architectures known as crypto-biometric systems, where cryptography and biometrics are merged to achieve high security and user convenience at the same time. In this paper, we explore the realization of a previously proposed cryptographic construct, called fuzzy vault, with the fingerprint minutiae data. This construct aims to secure critical data (e.g., secret encryption key) with the fingerprint data in a way that only the authorized user can access the secret by providing the valid fingerprint. The results show that 128-bit AES keys can be secured with fingerprint minutiae data using the proposed system.

Practical biometric authentication with template protection

Abstract: In this paper we show the feasibility of template protecting biometric authentication systems In particular, we apply template protection schemes to fingerprint data Therefore we first make a fixed length representation of the fingerprint data by applying Gabor filtering Next we introduce the reliable components scheme In order to make a binary representation of the fingerprint images we extract and then quantize during the enrollment phase the reliable components with the highest signal to noise ratio Finally, error correction coding is applied to the binary representation It is shown that the scheme achieves an EER of approximately 42% with secret length of 40 bits in experiments

A biometric identification system based on eigenpalm and eigenfinger features

Abstract: This paper presents a multimodal biometric identification system based on the features of the human hand. We describe a new biometric approach to personal identification using eigenfinger and eigenpalm features, with fusion applied at the matching-score level. The identification process can be divided into the following phases: capturing the image; preprocessing; extracting and normalizing the palm and strip-like finger subimages; extracting the eigenpalm and eigenfinger features based on the K-L transform; matching and fusion; and, finally, a decision based on the (k, l)-NN classifier and thresholding. The system was tested on a database of 237 people (1,820 hand images). The experimental results showed the effectiveness of the system in terms of the recognition rate (100 percent), the equal error rate (EER = 0.58 percent), and the total error rate (TER = 0.72 percent).

User authentication through typing biometrics features

Abstract: 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.

Experiments with an improved iris segmentation algorithm

Abstract: Iris is claimed to be one of the best biometrics. We have collected a large data set of iris images, intentionally sampling a range of quality broader than that used by current commercial iris recognition systems. We have re-implemented the Daugman-like iris recognition algorithm developed by Masek. We have also developed and implemented an improved iris segmentation and eyelid detection stage of the algorithm, and experimentally verified the improvement in recognition performance using the collected dataset. Compared to Masek's original segmentation approach, our improved segmentation algorithm leads to an increase of over 6% in the rank-one recognition rate.

Combining cryptography with biometrics effectively

Abstract: We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A well-known difficulty has been how to cope with the 10 to 20% of error bits within an iris code and derive an errorfree key. To solve this problem, we carefully studied the error patterns within iris codes, and devised a two-layer error correction technique that combines Hadamard and Reed-Solomon codes. The key is generated from a subject’s iris image with the aid of auxiliary error-correction data, which do not reveal the key, and can be saved in a tamper-resistant token such as a smart card. The reproduction of the key depends on two factors: the iris biometric and the token. The attacker has to procure both of them to compromise the key. We evaluated our technique using iris samples from 70 different eyes, with 10 samples from each eye. We found that an error-free key can be reproduced reliably from genuine iris codes with a 99.5% success rate. We can generate up to 140 bits of biometric key, more than enough for 128-bit AES. The extraction of a repeatable binary string from biometrics opens new possible applications, where a strong binding is required between a person and cryptographic operations. For example, it is possible to identify individuals without maintaining a central database of biometric templates, to which privacy objections might be raised.

Biometric template security: Challenges and solutions

Abstract: A biometric system is vulnerable to a variety of attacks aimed at undermining the integrity of the authentication process. These attacks are intended to either circumvent the security afforded by the system or to deter the normal functioning of the system. We describe the various threats that can be encountered by a biometric system. We specifically focus on attacks designed to elicit information about the original biometric data of an individual from the stored template. A few algorithms presented in the literature are discussed in this regard. We also examine techniques that can be used to deter or detect these attacks. Furthermore, we provide experimental results pertaining to a hybrid system combining biometrics with cryptography, that converts traditional fingerprint templates into novel cryptographic structures.

System for biometric security using a fob

Abstract: The present invention discloses a system and methods for biometric security using biometrics in a transponder-reader system. The biometric security system also includes a biometric sensor that detects biometric samples and a device for verifying biometric samples. In one embodiment, the biometric security system includes a transponder configured with a biometric sensor. In another embodiment, the system includes a reader configured with a biometric sensor. The device for verifying samples compares the biometric samples with information stored on databases.

A principled approach to score level fusion in multimodal biometric systems

Abstract: A multimodal biometric system integrates information from multiple biometric sources to compensate for the limitations in performance of each individual biometric system We propose an optimal framework for combining the matching scores from multiple modalities using the likelihood ratio statistic computed using the generalized densities estimated from the genuine and impostor matching scores The motivation for using generalized densities is that some parts of the score distributions can be discrete in nature; thus, estimating the distribution using continuous densities may be inappropriate We present two approaches for combining evidence based on generalized densities: (i) the product rule, which assumes independence between the individual modalities, and (ii) copula models, which consider the dependence between the matching scores of multiple modalities Experiments on the MSU and NIST multimodal databases show that both fusion rules achieve consistently high performance without adjusting for optimal weights for fusion and score normalization on a case-by-case basis

Cancelable key-based fingerprint templates

Abstract: Biometric based authentication can provide strong security guarantee about the identity of users. Security of biometric data is particularly important as compromise of the data will be permanent. Cancelable biometrics store a non–invertible transformed version of the biometric data and so if the storage is compromised the biometric data remains safe. Cancelable biometrics also provide a higher level of privacy by allowing many templates for the same biometric data and hence non-linkability of user’s data stored in different databases. We define how to measure the success of a particular transformation and matching algorithm for fingerprints. We consider a key–dependent geometric transform that is applied to the features extracted from a fingerprint, to generate a key–dependent cancelable template for the fingerprint. We investigate performance of an authentication system that uses this cancelable fingerprint when a fingerprint matching algorithm is used for detection. We evaluate performance of the system and show the challenges of achieving good performance if the matching algorithm is not modified.

A secure biometric authentication scheme based on robust hashing

Abstract: In this paper, we propose a secure biometric based authentication scheme which fundamentally relies on the use of a robust hash function. The robust hash function is a one-way transformation tailored specifically for each user based on their biometrics. The function is designed as a sum of properly weighted and shifted Gaussian functions to ensure the security and privacy of biometric data. We discuss various design issues such as scalability, collision-freeness and security. We also provide test results obtained by applying the proposed scheme to ORL face database by designating the biometrics as singular values of face images.

Multimodal biometric platform

Abstract: A multimodal biometric identification or authentication system includes a plurality of biometric clients. Each of the biometric clients may include devices for capturing biometric images of a plurality of types. The system includes a router in communication with the biometric clients. The router receives biometric images from, and returns biometric scores or results to, the biometric clients. The system includes a plurality of biometric matching engines in communication with the router. Each biometric matching engine includes multiple biometric processors. Each biometric processor is adapted to process biometric data of a particular type. The biometric matching engines transmit and receive biometric data to and from the router.

Multispectral imaging biometrics

Abstract: Methods and systems are provided for performing a biometric measurement on an individual. A purported skin site of the individual is illuminated under a plurality of distinct optical conditions during a single illumination session. Light scattered beneath a surface of the purported skin site is received separately for each of the plurality of distinct optical conditions. A multispectral image of the purported skin site is derived from the received light. A biometric function is performed with the derived multispectral image.

Open set face recognition using transduction

Abstract: This paper motivates and describes a novel realization of transductive inference that can address the open set face recognition task. Open set operates under the assumption that not all the test probes have mates in the gallery. It either detects the presence of some biometric signature within the gallery and finds its identity or rejects it, i.e., it provides for the "none of the above" answer. The main contribution of the paper is open set TCM-kNN (transduction confidence machine-k nearest neighbors), which is suitable for multiclass authentication operational scenarios that have to include a rejection option for classes never enrolled in the gallery. Open set TCM-kNN, driven by the relation between transduction and Kolmogorov complexity, provides a local estimation of the likelihood ratio needed for detection tasks. We provide extensive experimental data to show the feasibility, robustness, and comparative advantages of open set TCM-kNN on open set identification and watch list (surveillance) tasks using challenging FERET data. Last, we analyze the error structure driven by the fact that most of the errors in identification are due to a relatively small number of face patterns. Open set TCM-kNN is shown to be suitable for PSEI (pattern specific error inhomogeneities) error analysis in order to identify difficult to recognize faces. PSEI analysis improves biometric performance by removing a small number of those difficult to recognize faces responsible for much of the original error in performance and/or by using data fusion.

Wireless handheld device with local biometric authentication

Abstract: The invention is directed to a wireless handheld device that securely accesses one or more remote devices subject to locally authenticating a user via biometrics. The device may be implemented as a wireless mouse with a biometric sensor incorporated with a scroll wheel that captures a biometric from the user and authenticates the user to the device using the captured biometric. More specifically, the captured biometric is compared to a template stored in memory. The device transmits a wireless signal, such as a command stream including the user's user name and password, to access the remote devices when the captured biometric matches the template. However, the device does not operate when the user is not authenticated. Accordingly, the invention may be particularly useful to log-on and log-off a user who frequently leaves and returns to a personal computer or various remote devices during the course of a day.

Empirical Evaluation of Advanced Ear Biometrics

Abstract: We present results of the largest experimental investigation of ear biometrics to date. Approaches considered include a PCA ("eigen-ear") approach with 2D intensity images, achieving 63.8% rank-one recognition; a PCA approach with range images, achieving 55.3% Hausdorff matching of edge images from range images, achieving 67.5% and ICP matching of the 3D data, achieving 98.7%. ICP based matching not only achieves the best performance, but also shows good scalability with size of dataset. The data set used represents over 300 persons, each with images acquired on at least two different dates. In addition, the ICP-based approach is further applied on an expanded data set of 404 subjects, and achieves 97.5% rank one recognition rate. In order to test the robustness and variability of ear biometrics, ear symmetry is also investigated. In our experiments around 90% of people’s right ear and left ear are symmetric.

Vulnerabilities in biometric encryption systems

Abstract: The goal of a biometric encryption system is to embed a secret into a biometric template in a way that can only be decrypted with a biometric image from the enroled person. This paper describes a potential vulnerability in such systems that allows a less-than-brute force regeneration of the secret and an estimate of the enrolled image. This vulnerability requires the biometric comparison to “leak” some information from which an analogue for a match score may be calculated. Using this match score value, a “hill-climbing” attack is performed against the algorithm to calculate an estimate of the enrolled image, which is then used to decrypt the code. Results are shown against a simplified implementation of the algorithm of Soutar et al. (1998).

Monitoring activity using video information

Abstract: Apparatus and methods for monitoring activity use video information to track activity of a target at a given location. In an embodiment, the target is segmented into portions and a value of a biometric attribute is associated with the target and compared against values of a biometric attributes of corresponding portions of other images to identify the target and determine a length of time that the target is at the given location.

Data security system

Abstract: A data security system comprises a host processor, and a plurality of remote computers. Each remote computer provides biometric authentication of a user prior to responding to the user request for data access. The remote computers are handheld when in operational mode. A sensor in the handheld computer captures a biometric image while the remote computer is being used. The biometric sensor is positioned in such a way that the sensor enables the capture of the biometric image continually during computer usage with each request for access to secure data. The biometric authentication occurs in a seamless manner and is incidental to the data request enabling user identity authentication with each request to access secure data.

Data fusion in biometrics

Abstract: Any biometric system has drawbacks and cannot warranty 100% identification rates, nor 0% false acceptance and rejection ratios. One way to overcome the limitations is through a combination of different biometric systems. In addition, a multimodal biometric recognition is more difficult to fool than a single, biometric system, because it is more unlikely to defeat two or three biometric systems than one. This paper summarizes the different data fusion levels, and how it must be performed in order to improve the results of each combined system on its own

Ear Biometrics Based on Geometrical Feature Extraction

Abstract: Biometrics identification methods proved to be very efficient, more natural and easy for users than traditional methods of human identification. In fact, only biometrics methods truly identify humans, not keys and cards they posses or passwords they should remember. The future of biometrics will surely lead to systems based on image analysis as the data acquisition is very simple and requires only cameras, scanners or sensors. More importantly such methods could be passive, which means that the user does not have to take active part in the whole process or, in fact, would not even know that the process of identification takes place. There are many possible data sources for human identification systems, but the physiological biometrics seem to have many advantages over methods based on human behaviour. The most interesting human anatomical parts for such passive, physiological biometrics systems based on images acquired from cameras are face and ear. Both of those methods contain large volume of unique features that allow to distinctively identify many users and will be surely implemented into efficient biometrics systems for many applications. The article introduces to ear biometrics and presents its advantages over face biometrics in passive human identification systems. Then the geometrical method of feature extraction from human ear images in order to perform human identification is presented.