Fingerprint-based Authentication Research Articles

Fingerprint-Based Authentication System for Time and Attendance Management

Aims: Taking student attendance manually and maintaining it for a long time is a difficult task as well as wastes a lot of time. In this paper an Educational Time and Attendance Management System (EduTAMS) that will record and manage the time and attendance of students in a university community was developed. Study Design : The system was implemented using C# and Microsoft SQL Server 2008, and was tested using electronic fingerprint scanner which was interfaced to the digital computer system for verifying studen t identity. Place and Duration of Study: The students of University of Agriculture Abeokuta, Nigeria fingerprint attendance were captured during the 2012 academic session. Methodology: The system comprises of four main modules namely; fingerprint capture, fingerprint processing, fingerprint matching and database while the deployment structure of the system also consists of four major segments; Fingerprint Terminals, Database Server, Access Workstations and Network Service. EduTAMS uses fingerprint technolog y to authenticate every student. A fingerprint recognition system uses the distinctive and persistent characteristics from the ridges, also referred to as fingerprint features, to distinguish one person from another. Results: When eduTAM was compared with the manual method, the result shows that the average time taken per student using fingerprint based attendance and manual attendance register are 6.65 and 23.66 seconds respectively. Conclusion: The performance of the eduTAM system shows that it provide s robust, secured and automatic time and attendance management system for Students. Original Research Article

A generalized mixed model framework for assessing fingerprint individuality in presence of varying image quality

Fingerprint individuality refers to the extent of uniqueness of fingerprints and is the main criteria for deciding between a match versus nonmatch in forensic testimony. Often, prints are subject to varying levels of noise, for example, the image quality may be low when a print is lifted from a crime scene. A poor image quality causes human experts as well as automatic systems to make more errors in feature detection by either missing true features or detecting spurious ones. This error lowers the extent to which one can claim individualization of fingerprints that are being matched. The aim of this paper is to quantify the decrease in individualization as image quality degrades based on fingerprint images in real databases. This, in turn, can be used by forensic experts along with their testimony in a court of law. An important practical concern is that the databases used typically consist of a large number of fingerprint images so computational algorithms such as the Gibbs sampler can be extremely slow. We develop algorithms based on the Laplace approximation of the likelihood and infer the unknown parameters based on this approximate likelihood. Two publicly available databases, namely, FVC2002 and FVC2006, are analyzed from which estimates of individuality are obtained. From a statistical perspective, the contribution can be treated as an innovative application of Generalized Linear Mixed Models (GLMMs) to the field of fingerprint-based authentication.

A non-invertible cancellable fingerprint construct based on compact minutiae patterns

This paper proposes a new, privacy-preserving fingerprint construct, which consists of a single pattern created from a small subset of minutiae from the corresponding minutiae template. The sparsity of the resulting feature vector ensures that it cannot be used to reconstruct the underlying fingerprint image, while simultaneously allowing for the cancellability of compromised patterns. The proposed construct is, therefore, inherently a non-invertible cancellable fingerprint template protection scheme. Experimental results on the recognition accuracy of patterns consisting of three, four, and five minutiae were very encouraging: an FRR of 0.4% or less was achieved for all three pattern sizes, while the FAR ranged from 2.1% for 5-minutia patterns to 6.5% for 3-minutia patterns. It took about 0.1 seconds to verify a single person, regardless of the pattern size. These results suggest that the proposed fingerprint construct is suitable for deployment in fingerprint-based civilian authentication applications.

An empirical evaluation of rotation invariance of LDP feature for fingerprint matching using neural networks

Fingerprint-based individual authentication has been the most trusted and tested biometric among the biometrics traits. In the past two decades, many methods have been developed for fingerprint matching, but still there is a huge scope of improvement. This paper presents the rotation invariant fingerprint matching method, which is based on local directional pattern (LDP) features computed directly from grey values of a fingerprint image. For matching the extracted LDP histogram features, we have used single hidden layer feedforward neural networks (SLFNN). Six training algorithms namely, resilient propagation (RP), scaled conjugate gradient (SCG), gradient decent with all four variants [GD, GDM, GDA, GDX (refer to Table 2 for details)] are used for evaluating the matching performance and convergence time. The results show that the proposed features are invariant to the rotation and also suitable for fingerprint matching using SLFNN. The results also demonstrate that RP is better in performance than other investigated algorithms.

Implementation of Fingerprint Assist Wending Machine with Recharge Option

In this paper we propose an implementation technique for coffee vending machine with the goal of getting recharge option for customer using fingerprint-based authentication. We implement the proposed design based on Advance Virtual RISC (AVR) microcontroller. The circuit is tested and compared with the existing embedded technology. Among the various biometric traits (e.g., face, iris, fingerprint, voice), Fingerprint-based authentication has the longest history, and has been successfully adopted in both forensic and civilian applications. Advances in fingerprint capture technology have resulted in new large scale civilian applications. The purpose of this article is to give an overview of fingerprint-based recognition and discuss research opportunities for making these systems perform more effectively.

Biometric encryption using enhanced finger print image and elliptic curve

Biometrics, cryptography and data hiding will provide good perspectives for information security Bodo, 1994. The information security mainly depends on the secret key. In this paper, the issues related with key management of cryptosystem Gao, 2010 is addressed by providing biometrics-based Jain et al., 2007 key generation which is never stored or revealed to the authentication server. Finger print is widely used than the iris or face and more over it is the primary choice for most privacy concerned applications. Fingerprint-based authentication with randomly selected 40 minutiae is sufficient to generate the key. Elliptic curve is the best solution for cryptography Miller, 1986. The proposed work deals about, how the image quality can be improved by introducing image fusion technique at sensor levels. The results of the images after introducing the decision rule based image fusion technique are evaluated and analysed with its entropy levels and root mean square error. Then the resultant enhanced image is used for extracting the key for ECC applications.

A Fingerprint-based Authentication Framework for ATM Machines

A Fingerprint-based Authentication Framework for ATM Machines The security of the transactions on the Automated Teller Machine (ATM) has been raising many concerns in some parts of the world. These concerns are due to series of limitations in the existing designs of the various service points. The current use of Personal Identification Number (PIN) for ATM user’s verification and identification has been susceptible to unauthorized access, misplacement, forgetfulness, card swallowing among others; thereby narrowing down the machine’s acceptability and patronage. In this paper, a framework for fingerprint authenticated ATM application is presented. The framework comprises of modules for fingerprint enrolment, database and verification. The verification module comprises of fingerprint enhancement, feature extraction and matching sub-modules, which all rely on suitable mathematical models to function. There is also platform for financial transaction including withdrawal and balance enquiries. The implementation was carried out using Windows 7 as operational platform while C# and Microsoft SQL server served as the frontend and backend engines respectively. Tests conducted on the evaluation of the application using False Rejection Rate (FRR), False Acceptance Rate (FAR) and Average Matching Time (AMT) show the adequacy and the suitability of the proposed framework for ATM user verification and authentication.

A fingerprint-based audio authentication scheme using frequency domain statistical characteristic

Recently, a major problem faced by digital data providers and owners is protecting data from malicious falsification and distribution. As a solution to this problem, digital fingerprinting technique is now attracting attention as new method for integrity protection. According to frequency domain statistical characteristic, an efficient fingerprint-based audio authentication scheme is proposed in this paper. Initially, the host audio signal is equally divided into non-overlapping frames, moreover, each audio frame is then equally split into non-overlapping segments, and the DFT (discrete Fourier transform) domain relation of each audio segment is computed. Then DFT domain relations of each audio frame are adopted to generate the corresponding binary pattern using non-uniform quantization. Finally, the fingerprint is obtained by performing XOR operation between the binary pattern and binary pseudo-random sequence. Simulation results demonstrate the effectiveness of our scheme in terms of inaudibility, detection reliability, robustness against some non-malicious signal processing operations and vulnerability against malicious falsification.

Intrinsic Physical-Layer Authentication of Integrated Circuits

Radio-frequency distinct native attribute (RF-DNA) fingerprinting is adapted as a physical-layer technique to improve the security of integrated circuit (IC)-based multifactor authentication systems. Device recognition tasks (both identification and verification) are accomplished by passively monitoring and exploiting the intrinsic features of an IC's unintentional RF emissions without requiring any modification to the device being analyzed. Device discrimination is achieved using RF-DNA fingerprints comprised of higher order statistical features based on instantaneous amplitude, phase, and frequency responses as a device executes a sequence of operations. The recognition system is trained using multiple discriminant analysis to reduce data dimensionality while retaining class separability, and the resultant fingerprints are classified using a linear Bayesian classifier. Demonstrated identification and verification performance includes average identification accuracy of greater than 99.5% and equal error rates of less than 0.05% for 40 near-identical devices. Depending on the level of required classification accuracy, RF-DNA fingerprint-based authentication is well-suited for implementation as a countermeasure to device cloning, and is promising for use in a wide variety of related security problems.

FPGA-based Personal Authentication Using Fingerprints

The current technological age demands the deployment of biometric security systems not only in those stringent and highly reliable fields (forensic, government, banking, etc.) but also in a wide range of daily use consumer applications (internet access, border control, health monitoring, mobile phones, laptops, etc.) accessible worldwide to any user. In order to succeed in the exploitation of biometric applications over the world, it is needed to make research on power-efficient and cost-effective computational platforms able to deal with those demanding image and signal operations carried out in the biometric processing. The present work deals with the evaluation of alternative system architectures to those existing PC (personal computers), HPC (high-performance computing) or GPU-based (graphics processing unit) platforms in one specific scenario: the physical implementation of an AFAS (automatic fingerprint-based authentication system) application. The development of automated fingerprint-based personal recognition systems in the way of compute-intensive and real-time embedded systems under SoPC (system-on-programmable-chip) devices featuring one general-purpose MPU (microprocessor unit) and one run-time reconfigurable FPGA (field programmable gate array) proves to be an efficient and cost-effective solution. The provided flexibility, not only in terms of software but also in terms of hardware thanks to the programmability and run-time reconfigurability performance exhibited by the suggested FPGA device, permits to build any application by means of hardware-software co-design techniques. The parallelism and acceleration performances inherent to the hardware design and the ability of reusing hardware resources along the application execution time are key factors to improve the performance of existing systems.

SCAN secure processor and its biometric capabilities

This paper presents the design of the SCAN secure processor and its extended instruction set to enable secure biometric authentication. The SCAN secure processor is a modified SparcV8 processor architecture with a new instruction set to handle voice, iris, and fingerprint-based biometric authentication. The algorithms for processing biometric data are based on the local global graph methodology. The biometric modules are synthesized in reconfigurable logic and the results of the field-programmable gate array (FPGA) synthesis are presented. We propose to implement the above-mentioned modules in an off-chip FPGA co-processor. Further, the SCAN-secure processor will offer a SCAN-based encryption and decryption of 32 bit instructions and data.

Pair-polar coordinate-based cancelable fingerprint templates

Fingerprint-based authentication has been widely implemented, however, security and privacy of fingerprint templates still remain an issue. Some schemes have been proposed to protect fingerprint templates, such as the design of cancelable fingerprint templates. Yet, most of the existing schemes rely on accurate fingerprint image registration, which is very hard to achieve, especially considering the need to avoid storing any information related to the raw fingerprint features. In this paper, a pair-polar coordinate-based template design method is developed which does not need registration. The proposed scheme explores the relative relationship of minutiae in a rotation- and shift-free pair-polar framework. A many-to-one mapping is applied to ensure the non-invertible recovery of raw templates. A random translation parameter is introduced to further distort the minutia distribution. Under various scenarios, the proposed scheme is evaluated using the public databases, FVC2002DB1, FVC2002DB2 and FVC2002DB3. The experiment results show that the new method satisfies the template protection requirements and the performance degradation caused by the transformation is very low.

Fingerprint Image Processing Acceleration Through Run-Time Reconfigurable Hardware

To the best of the authors' knowledge, this is the first brief that implements a complete automatic fingerprint-based authentication system (AFAS) application under a dynamically partial self-reconfigurable field-programmable gate array (FPGA). The main benefits of this implementation are the acceleration of the processing reached by the parallelism inherent to the hardware design, the high level of integration, the consequent security and reliability improvements provided by the usage of a system-on-programmable-chip device that is able to embed the main components of the application in a single chip, and the low cost achieved by the whole system due to the reconfigurability performance featured by the suggested FPGA. All these factors result in an outstanding system that is able to authenticate the identity of any user by means of those distinctive characteristics available in fingerprints. This brief reveals the advantages of run-time reconfigurable hardware in the implementation of those embedded systems demanding real-time performance at low cost. The minimization of the reconfiguration overhead by means of the proper sizing of the reconfigurable region in the FPGA and the design of a hardware configuration controller that is able to reach the maximum configuration rates allowed by the technology (3.2 Gb/s) are key factors to succeed in the development of the embedded AFAS application. The proposed system, which is implemented by means of hardware-software co-design techniques under a Virtex4 XC4VLX25 FPGA working at 100 MHz, is able to overcome in one order of magnitude the execution time performance achieved by a personal computer platform based on an Intel Core2Duo microprocessor running at 1.83 GHz.

Biometrics-based consumer applications driven by reconfigurable hardware architectures

Nowadays the development of automatic biometrics-based personal recognition systems is a reality in the current technological age. Not only those applications demanding stringent security levels but also many daily use consumer applications request the existence of high performance computational platforms in charge of recognizing the identity of an individual based on the analysis of his/her physiological or behavioural characteristics. The state of the art points out two main open problems in the implementation of such automatic applications: on the one hand, the needed improvement of the reliability level of the existing recognition systems in terms of accuracy, security and real-time performances; on the other hand, the cost reduction of those physical platforms in charge of the processing. This work addresses those limitations of current systems and aims at finding the proper system architecture to develop this kind of high-performance applications at low cost. Because of that, those existing solutions based on expensive multiprocessor systems like HPC (High Performance Computer), GPU (Graphics Processing Unit), or PC (Personal Computer) platforms need to be discarded, and instead of them embedded system solutions based on programmable logic devices are suggested in this work. The programmability performances of FPGA (Field Programmable Gate Array) devices together with the inherent parallelism of hardware design provide the needed flexibility to develop made-to-measure coprocessors in charge of accelerating those time-critical computational tasks. To address the cost of the system, dynamically reconfigurable FPGAs are suggested in this work. The scheduling of the recognition application into a series of mutually exclusive tasks, and the reutilization of those functional resources available in the FPGA by multiplexing different coprocessors in the same area along the application execution time allows reducing the size of the device and therefore its cost at the expense of the reconfiguration overhead. The hardware–software co-design of an AFAS (automatic fingerprint-based authentication system) under two different run-time reconfigurable platforms is presented as the proof of concept of the suggested architecture. The outstanding results achieved in this work pave the way for the implementation of biometric applications by means of run-time reconfigurable FPGAs.

Intersubject Differences in False Nonmatch Rates for a Fingerprint-Based Authentication System

The intersubject dependencies of false nonmatch rates were investigated for a minutiae-based biometric authentication process using single enrollment and verification measurements. A large number of genuine comparison scores were subjected to statistical inference tests that indicated that the number of false nonmatches depends on the subject and finger under test. This result was also observed if subjects associated with failures to enroll were excluded from the test set. The majority of the population (about 90%) showed a false nonmatch rate that was considerably smaller than the average false nonmatch rate of the complete population. The remaining 10% could be characterized as goats due to their relatively high probability for a false nonmatch. The image quality reported by the template extraction module only weakly correlated with the genuine comparison scores. When multiple verification attempts were investigated, only a limited benefit was observed for goats, since the conditional probability for a false nonmatch given earlier nonsuccessful attempts increased with the number of attempts. These observations suggest that (1) there is a need for improved identification of goats during enrollment (e.g., using dedicated signal-driven analysis and classification methods and/or the use of multiple enrollment images) and (2) there should be alternative means for identity verification in the biometric system under test in case of two subsequent false nonmatches.

A fingerprint-based user authentication protocol considering both the mobility and security in the telematics environment

With the advance of the Internet and mobile communication techniques, the telematics environment where users in vehicles can use the Internet service has been realized. For the safe driving, however, we propose that user authentication for the Internet service is performed by using the driver's fingerprint, instead of typing his/her password. Since the driver's fingerprint is private information to be protected and the size of the fingerprint information is much larger than that of a typical password, we need a different user authentication protocol for the telematics environment. That is, in addition to the compliance with the standard X9.84 protocol to protect the fingerprint information transmitted, we use the watermarking technique to lessen the privacy threat, and propose a secure and efficient protocol between Access Points (APs) considering the possible hand-off during the authentication in the mobile telematics environment. Based on the experimental measurement of the proposed protocol, we confirm that the fingerprint-based user authentication can be performed in real-time in the telematics environment.

Fingerprint-Based Recognition

Biometric recognition, or biometrics, refers to the authentication of an individual based on her or his biometric traits. Among the various biometric traits (e.g., face, iris, fingerprint, voice), fingerprint-based authentication has the longest history, and it has been successfully adopted in both forensic and civilian applications. Advances in fingerprint capture technology have resulted in new large-scale civilian applications (e.g., US–VISIT program); however, these systems still encounter difficulties due to various noise factors present in operating environments. The purpose of this article is to give an overview of fingerprint-based recognition and discuss research opportunities for making these systems perform more effectively.

Fingerprint-Based Identity Authentication and Digital Media Protection in Network Environment

Current information security techniques based on cryptography are facing a challenge of lacking the exact connection between cryptographic key and legitimate users. Biometrics, which refers to distinctive physiological and behavioral characteristics of human beings, is a more reliable indicator of identity than traditional authentication system such as passwords-based or tokens-based. However, researches on the seamless integration biometric technologies, e.g., fingerprint recognition, with cryptosystern have not been conducted until recent years. In this paper, we provide an overview of recent advancements in fingerprint recognition algorithm with a special focus on the enhancement of low-quality fingerprints and the matching of the distorted fingerprint images, and discuss two representative methods of key release and key generation scheme based on fingerprints. We also propose two solutions for the application in identity authentication without trustworthy thirdparty in the network environment, and application in digital media protection, aiming to assure the secrecy of fingerprint template and fingerprint-based user authentication.

A REMOTE AUTHENTICATION SYSTEM USING FINGERPRINTS

We present the design and implementation of a fingerprint-based remote authentication system. In this system, the fingerprint features captured at a client terminal are transmitted over a communication channel to a central server location where the verification takes place. In order to overcome replay attacks, we propose an original approach to fingerprint matching that relies on different fingerprint features for every execution of the authentication protocol. The paper also introduces an efficient approach for fingerprint image enhancement that constitutes the core of the feature extraction module included in the proposed authentication system. A public domain collection of fingerprint images is used to evaluate the system performance. The experimental results reveal that the proposed system can achieve good matching performance on this data collection and, furthermore, is able to accurately reject replay attacks.