Fingerprint Template Research Articles

Electronic Data Management for Vaccine Trials in Low Resource Settings: Upgrades, Scalability, and Impact of ODK.

Background: ODK provides software and standards that are popular solutions for off-grid electronic data collection and has substantial code overlap and interoperability with a number of related software products including CommCare, Enketo, Ona, SurveyCTO, and KoBoToolbox. These tools provide open-source options for off-grid use in public health data collection, management, analysis, and reporting. During the 2018–2020 Ebola epidemic in the North Kivu and Ituri regions of Democratic Republic of Congo, we used these tools to support the DRC Ministère de la Santé RDC and World Health Organization in their efforts to administer an experimental vaccine (VSV-Zebov-GP) as part of their strategy to control the transmission of infection.Method: New functions were developed to facilitate the use of ODK, Enketo and R in large scale data collection, aggregation, monitoring, and near-real-time analysis during clinical research in health emergencies. We present enhancements to ODK that include a built-in audit-trail, a framework and companion app for biometric registration of ISO/IEC 19794-2 fingerprint templates, enhanced performance features, better scalability for studies featuring millions of data form submissions, increased options for parallelization of research projects, and pipelines for automated management and analysis of data. We also developed novel encryption protocols for enhanced web-form security in Enketo.Results: Against the backdrop of a complex and challenging epidemic response, our enhanced platform of open tools was used to collect and manage data from more than 280,000 eligible study participants who received VSV-Zebov-GP under informed consent. These data were used to determine whether the VSV-Zebov-GP was safe and effective and to guide daily field operations.Conclusions: We present open-source developments that make electronic data management during clinical research and health emergencies more viable and robust. These developments will also enhance and expand the functionality of a diverse range of data collection platforms that are based on the ODK software and standards.

Cryptography based Internet Security ATM System using Fingerprint for securing PIN

Today, ATMs (automated teller machines) are used in a variety of ways, including: you can withdraw cash, transfer cash, check your balance, get an account summary, and more. The main component here is security, to maintain the security we prefer cryptography and biometrics. Cryptography is a state- of-the-art technique for increasing security. Using cryptography and biometrics together creates a bio cryptographic system. Since the private key is an important component of encryption, here one is the main task to secure the private [1] key. To overcome this issue, we use a biometric fingerprint image. However, biometrics cannot protect anyone’s fingerprint template because of the many suspected attacks. Therefore, we use a fuzzy vault system that combines cryptography [2] and biometrics [4] to ensure that only authorized users can use their passwords and PINs with the legal data. Keywords: Biometrics, Cryptography, Fuzzy vault system, IP security, Java Applets.

SPIN: A Blockchain-Based Framework for Sharing COVID-19 Pandemic Information across Nations

The COVID-19 pandemic has caused many countries around the globe to put strict policies and measures in place in an attempt to control the rapid spread of the virus. These measures have affected economic activities and have impacted a broad range of businesses, such as international traveling, restaurants, and shopping malls. As COVID-19 vaccination efforts progress, countries are starting to relax international travel constraints and permit passengers from certain destinations to cross the border. Moreover, travelers from those destinations are likely required to provide certificates of vaccination results or negative COVID-19 tests before crossing the borders. Implementing these travel guidelines requires sharing information between countries, such as the number of COVID-19 cases and vaccination certificates for travelers. In this paper, we introduce SPIN, a framework leveraging a permissioned blockchain for sharing COVID-19 information between countries. This includes public data, such as the number of vaccinated people, and private data, such as vaccination certificates for individuals. Additionally, we employ cancelable fingerprint templates to authenticate private information about travelers. We analyze the framework from scalability, efficiency, security, and privacy perspectives. To validate our framework, we provide a prototype implementation using the Hyperledger Fabric platform.

Cancelable Multimodal Biometrics Based on Chaotic Maps

Biometric authentication systems raise certain concerns with regard to security, violation of privacy, and storage issues of biometric templates. This paper proposes a protection approach of biometric templates storage in a multimodal biometric system while ensuring both the cancelability of biometric templates and the efficiency of the authentication process. We propose applying a chaotic maps-based transform on the biometric features to address the cancelability issue. We used Logistic map and Torus Automorphism to generate cancelable biometric features of the face and fingerprint minutia points, respectively. Both transformed features would be concatenated and saved in the database of the system instead of the original features. In the authentication stage, the similarity scores of both transformed face and fingerprint templates are computed and fused using the weighted sum rule. The results of the experimentation, conducted using images from the ORL face and FVC2002 DB1 fingerprint databases, demonstrated the higher performance of the proposed approach achieving a genuine accept rate equal to 100%. Moreover, the obtained results confirmed the soundness of the proposed cancelable technique to satisfy the biometric systems’ requirements (i.e., security, revocability, and diversity).

A Novel Minutiae Triangulation Technique for Non-invertible Fingerprint Template Generation

The fingerprint is the readily available and most widely used biometrics for the security of a system. In order to impart the security of the template database, it is important to make the fingerprint template robust to fingerprint reconstruction, i.e., invertibility. In this paper, a fingerprint template is proposed using a novel minutiae triangulation technique. In this triangulation technique, the set of minutiae of a template is taken to generate a set of minutiae triplets each forming a triangle. After this, a minutiae transformation is applied to obtain a set of triplets of internal angles of the triangle which also removes the minutiae location and orientation information. In the absence of this information, the orientation map of the fingerprint cannot be estimated. This set of triplets together with some other information is used as a proposed fingerprint template. The proposed system is experimented using standard FVC2000, FVC2004 and FVC2006 databases and yields better results in terms of EER (Equal Error Rate) as compared with the state-of-art techniques.

Fingerprint Template Protection Using Irreversible Minutiae Tetrahedrons

Abstract The use of fingerprint continues to increase constantly with the propagation of biometric authentication technologies. Fingerprint is today the most widely used biometric modality for human verification and identification, due to its practical use and its discriminative structure that allows to different identities to be easily distinguished. Unfortunately, this emergence has been accompanied by a number of problems and challenges related to identity theft and to security issues in general. To address these concerns, many approaches have been proposed in which only few of them were able to reach an acceptable level of both security and performance. In this paper, we propose a new fingerprint template protection scheme that enhances the security of protected system while preserving performance. The proposed approach is a minutiae-based technique that performs fingerprint matching in a transformed space using irreversible minutiae tetrahedrons. Using the original Fingerprint Verification Competition (FVC) protocol, the provided experimental results on FVC2002 DB1, DB2 and DB3 fingerprint databases have shown satisfactory recognition rates. Our results are compared to some existing techniques that use the same protocol of test. We have proved as well that the proposed scheme meets the requirements of revocability, unlinkability and irreversibility.

Design of cancelable MCC-based fingerprint templates using Dyno-key model

Minutia Cylinder Code (MCC) is an effective, high-quality representation of local minutia structures. MCC templates demonstrate fast and excellent fingerprint matching performance, but if compromised, they can be reverse-engineered to retrieve minutia information. In this paper, we propose alignment-free cancelable MCC-based templates by exploiting the MCC feature extraction and representation. The core component of our design is a dynamic random key model, called Dyno-key model. The Dyno-key model dynamically extracts elements from MCC’s binary feature vectors based on randomly generated keys. Those extracted elements are discarded after the block-based logic operations so as to increase security. Leveling with the performance of the unprotected, reproduced MCC templates, the proposed method exhibits competitive performance in comparison with state-of-the-art cancelable fingerprint templates, as evaluated over seven public databases, FVC2002 DB1-DB3, FVC2004 DB1 and DB2, and FVC2006 DB2 and DB3. The proposed cancelable MCC-based templates satisfy all the requirements of biometric template protection.

Design of a fingerprint template protection scheme using elliptical structures

Although biometric authentication is viewed as more prominent than password or token-based methodology in identity verification, biometric templates are vulnerable to attacks. This paper proposes a new approach for securing fingerprint templates using elliptical structures generated from the fingerprint minutiae. Authors generate a feature vector from the ellipse and will be projected onto a 3D-space to compute a binary string. The resultant binary string is transformed to frequency domain (DFT) and multiplied with a user specific random matrix to make it permanently non-invertible and secure. The results show the efficacy of the proposed method for protecting the fingerprints.

Securing fingerprint templates by enhanced minutiae‐based encoding scheme in Fuzzy Commitment

Fingerprint authentication has gained attention in recent years due to its distinctiveness, low-cost sensors, and user willingness to submit them. Its extensive deployment in our automated world raises major concerns regarding the secrecy of biometric templates and the privacy of rightful owners in biometric systems. Fuzzy Commitment (FC) focuses on securing the biometric templates by performing authentication based on the validity of secret keys from biometric features. However, the major challenge in designing Fingerprint-based FC is the requirement of efficient binary representation for unordered and variable minutiae points in fingerprint images. Additionally, its leakage can compromise an intrinsic characteristic of the individual. The paper proposes Fingerprint-based FC incorporating an encoding scheme dependent on the number and type of minutiae points present near the fingerprint's core point. The biometric templates are never identical thereby, this approach allows fuzziness in minutiae points by incorporating Bose–Chaudhuri–Hocquenghem (BCH) codes for error-correction and secures random codeword of the error-correcting scheme as secret key by SHA-256 hash mapping. The proposed approach is evaluated on FVC2000-DB2, FVC2002-DB1, FVC2002-DB2, and FVC2004-DB1, and the results illustrate the efficiency of the proposed scheme. Furthermore, the security analysis of stored helper data and hash mapping demonstrates that the proposed approach is secure.

An Improved Vehicle Registration and Licensing System

Vehicle registration and licensing systems have been in existence for decades. However, there has been over 55% increase in the number of reported stolen vehicles which have not been recovered in the last 3 years. Therefore, there is need to improve on its existing systems by incorporating anti-theft capability of vehicles using fingerprint biometric technology. In developing the Secured Vehicle Registration System (SVRS), data on vehicle registration, renewal and change of ownership procedures were collected from the Motor Licensing Office at Osogbo. Unified Modelling Language (UML) tools was used for the system design, to illustrate the whole system in a clearer way, and implemented using JavaScript, PHP scripting language, HTML, XAMPP SQLServer and the Mantra MFS100 fingerprint scanner. The system performance was evaluated by authenticating registered vehicle owner biometric to calculate the Accuracy, Average Response Time (ART) and Apdex Score. The result of the evaluation using 288 fingerprint templates of 72 vehicle owners shows the False Accept Rate (FAR) of 0.0% and False Reject Rate (FRR) of 2.1%, which is equivalent to a system accuracy of 97.9%. The ART for the fingerprint execution matching is 36.3 microseconds while the overall system satisfaction Apdex score recorded was 0.73, which denotes a satisfying system. The high-speed verification method uses the lowest computational power and execution time to deliver accurate results through making a match or non-match against stored templates. The developed system demonstrated its ability to link vehicle(s) to its respective owner(s) and also function as an automatic identity verification system for vehicle owners using VIN and fingerprint. The system has the ability to be employed for preventing fraudulent change of ownership and also help reduce delay in processing vehicle license.Keywords— authentication, biometrics, database, fraudulent, information protection, motor vehicle administration, motor vehicle registry, security code, vehicle owners

Producing secure multimodal biometric descriptors using artificial neural networks

With the rapidly growing use of biometric authentication systems, the security of these systems and the privacy of users have attracted significant attention in recent years. Multi-modal biometrics have been able to improve the accuracy of the system but require additional bandwidth to exchange the data. Fragile watermarking has been used to allow the transmission of both biometric templates using the amount of data required to transmit one of them, that is, the cover image, while securing these templates against attacks. Despite the high accuracy of these systems, communicating such templates imposes risks towards the privacy of the users. In this study, a new method is proposed to generate fixed-size descriptors for the face and fingerprint templates, including the timestamp of the transmission and a unique system identifier. The inclusion of the timestamp enables the system to detect and deny replay attacks, while the unique system identifier maintains the privacy of the users. The experiments conducted to evaluate the proposed method have shown that the proposed method has been able to achieve these features while maintaining high recognition rates, 99.41% and 99.32%, similar to the use of the entire biometric templates in the matching stage.

AN ADAPTIVE ALGORITHM BASED AUTHENTICATION SYSTEM FOR REAL-TIME BIOMETRIC TIME-ATTENDANCE SYSTEM

Biometric features are physical and biological characteristics that are unique to a person and can be used to accomplish authentication based on the particular modality. The main purpose of implementation of an Adaptive auto-correction technique for biometric time-attendance system is to improve the matching rate of fingerprint verification under the condition when fingerprint patterns vary due to environmental parameter like temperature. An Adaptive auto-correction technique is proposed which auto-corrects the reference fingerprint template at the time of genuine user rejection. The proposed technique is implemented on commercially available biometric device which uses Innovatrics, a standard commercially available extractor and matcher. Evaluation is carried out on 250 fingerprint templates of 10-users captured at varying temperature from 250C to 00C. The experimental analysis will be carried out to improve the recognition rate.

A Digital Geometry-Based Fingerprint Matching Technique

Fingerprint authentication systems have become ubiquitous with the event of smart devices and cheap sensors. Because of its use in a wide range of devices, it is important that the biometric authentication systems are computationally cheap, and at the same time robust to distortions and noises. Most of the existing fingerprint authentication systems are based on conventional mathematics or complex filter and consequently features extracted are computationally expensive or gross approximate with a large margin of errors leading to drops in the accuracy of the system. In this paper, we propose a fingerprint template based on translation and rotation invariant features of the delaunay triangulation of minutiae. However existing methods of comparison of delaunay triangles features do not always result in an optimum match because of the distortion in the different prints of the same finger. In the proposed method, features extracted from the delaunay triangulation are augmented with the information of local ridges based on discrete curvature and digital straightness. Experimentation with FVC2000 shows that the proposed method has better performances compared to the latest techniques.

A non‐invertible transformation based technique to protect a fingerprint template

AbstractA fingerprint‐based authentication system provides security to the applications of numerous fields and usually stores minutiae information in the database as a template. It has been observed from the literature that the reconstruction of an original fingerprint is possible from minutiae points information; hence the security of the stored template becomes extremely crucial. Cancellable biometric techniques based on non‐invertible transformation protect the stored template. These techniques prevent the reconstruction of original fingerprint data from the compromised template and avoid unauthorized access to the system. In this paper, a technique based on the non‐invertible transformation to protect a fingerprint template is proposed. In the technique, minutiae locations in a fingerprint are transformed by using the minutiae's original locations and orientation information, and a user keyset. A principal component analysis based approach to align the probe and gallery templates of fingerprint images while matching is also proposed. The evaluation of the proposed technique is carried out on seven different fingerprint databases taken from FVC2000, FVC2002, and FVC2004 databases, and its performance is compared with other existing state‐of‐the‐art techniques in the literature. The comparative performance shows that the proposed technique is highly robust and performs exceptionally well compared to other existing techniques.

Efficient and Secure Cancelable Biometric Authentication Framework Based on Genetic Encryption Algorithm

Various cancelable biometric techniques have been proposed to maintain user data security. In this work, a cancelable biometric framework is introduced to satisfy user data security and keeping the original biometric template safe away from intruders. Thus, our main contribution is presenting a novel authentication framework based on the evolutionary Genetic Algorithm (GA)-based encryption technique. The suggested framework produces an entirely unrecognized biometric template by hiding the whole discriminative features of biometric templates; this is with exploiting the outstanding characteristics of the employed Genetic operations of the utilized encryption technique. Firstly, the GA initiates its search from a population of templates, not a single template. Secondly, some statistical operators are used to exploit the resulting initial population to generate successive populations. Finally, the crossover and mutation operations are performed to produce the ultimate cancelable biometric templates. Different biometric databases of the face and fingerprint templates are tested and analyzed. The proposed cancelable biometric framework achieves appreciated sensitivity and specificity results compared to the conventional OSH (Optical Scanning Holography) algorithm. It accomplishes recommended outcomes in terms of the AROC (Area under the Receiver Operating Characteristic) and the probability correlation distribution between the original biometrics and the encrypted biometrics stored in the database. The experimental results prove that the proposed framework achieves excellent results even if the biometric system suffers from different noise ratios. The proposed framework achieves an average AROC value of 0.9998, an EER (Equal Error Rate) of 2.0243×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> , FAR (False Acceptance Rate) of 4.8843×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> , and FRR (False Rejection Rate) of 2.2693×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-4</sup> .

Compact and Cancelable Fingerprint Binary Codes Generation via One Permutation Hashing

Representing fingerprint templates in binary form can provide outstanding merits compared to the conventional minutiae-based fingerprint recognition system. The existing fixed-length fingerprint feature extraction methods either suffer from redundant feature magnitude or lack of template security. In this letter, we present a compact (128 bytes) and cancelable fingerprint binary codes generation scheme which enables accurate and efficient comparison as well as high security. This binary representation is also available for advanced encryption schemes (e.g., fuzzy commitment). Specifically, a kernel learning-based real-valued fingerprint feature is converted into compact and cancelable binary code via one permutation hashing. A partial Haar transform is deployed to further strengthen the irreversibility of the whole system. Experimental results on six benchmark datasets FVC2002 and FVC2004 coupled with security analysis demonstrate the superiority of the proposed method compared with several state-of-the-arts.

Individual identification of electronic equipment based on electromagnetic fingerprint characteristics

With the rapid development of communication and computer, the individual identification technology of communication equipment has been brought to many application scenarios. The identification of the same type of electronic equipment is of considerable significance, whether it is the identification of friend or foe in military applications, identity determination, radio spectrum management in civil applications, equipment fault diagnosis, and so on. Because of the limited-expression ability of the traditional electromagnetic signal representation methods in the face of complex signals, a new method of individual identification of the same equipment of communication equipment based on deep learning is proposed. The contents of this paper include the following aspects: (1) Considering the shortcomings of deep learning in processing small sample data, this paper provides a universal and robust feature template for signal data. This paper constructs a relatively complete signal template library from multiple perspectives, such as time domain and transform domain features, combined with high-order statistical analysis. Based on the inspiration of the image texture feature, characteristics of amplitude histogram of signal and the signal amplitude co-occurrence matrix (SACM) are proposed in this paper. These signal features can be used as a signal fingerprint template for individual identification. (2) Considering the limitation of the recognition rate of a single classifier, using the integrated classifier has achieved better generalization ability. The final average accuracy of 5 NRF24LE1 modules is up to 98% and solved the problem of individual identification of the same equipment of communication equipment under the condition of the small sample, low signal-to-noise ratio.

A novel fingerprint template protection and fingerprint authentication scheme using visual secret sharing and super-resolution

Fingerprint is the most recommended and extensively practicing biometric trait for personal authentication. Most of the fingerprint authentication systems trust minutiae as the characteristic for authentication. These characteristics are preserved as fingerprint templates in the database. However, it is observed that the databases are not secure and can be negotiated. Recent studies reveal that, if a person’s minutiae points are dripped, fingerprint can be restored from these points. Similarly, if the fingerprint records are lost, it is a permanent damage. There is no mechanism to replace the fingerprint as it is part of the human body. Hence there is a necessity to secure the fingerprint template in the database. In this paper, we introduce a novel fingerprint template protection and fingerprint authentication scheme using visual secret sharing and super-resolution. During enrollment, a secret fingerprint image is encrypted into n shares. Each share is stored in a distinct database. During authentication, the shares are collected from various databases. The original secret fingerprint image is restored using a multiple image super-resolution procedure. The experimental results show that the reconstructed fingerprints are similar to the original fingerprints. The proposed method is robust, secure, and efficient in terms of fingerprint template protection and authentication.

Biometric key generation based on generated intervals and two-layer error correcting technique

As for a biometric key, key management and biometric data security are both important. Existing bio-key generation methods are usually based on the biometric templates or features directly, it may expose user’s biometric data and will further make the biometric data permanently unusable for his secure identification recognitions. In this paper, a fingerprint bio-key generation approach using the feature distance is proposed. We utilize the relative distances among user’s fingerprint minutiae to generate a unique bio-key. Such bio-key is determinable and recoverable via the generation interval scheme. In addition, we use a two-layer error correcting technique to guarantee a better reliability during the data transmission. The experimental results positively show that our approach can ensure higher security of the bio-key and guarantee a good key regeneration rate. Besides, the storage of the original bio-key or any fingerprint template is unnecessary.

Alignment-free cancelable fingerprint templates with dual protection

Cancelable biometrics is an important biometric template protection technique. However, many existing cancelable fingerprint templates suffer post-transformation performance deterioration and the attacks via record multiplicity (ARM). In this paper, we design alignment-free cancelable fingerprint templates with dual protection, which is composed of the window-shift-XOR model and the partial discrete wavelet transform. The former defuses the ARM threat and is combined with the latter to provide dual protection and enhance matching performance. The designed cancelable templates meet the requirements of non-invertibility, diversity and revocability and demonstrate superior recognition accuracy, when evaluated over public databases; for example, the Equal Error Rate of the proposed method in the lost-key scenario under the 1vs1 protocol is 0% for both FVC2002 DB1 and DB2, 1.63% for FVC2002 DB3, 7.35% for FVC2004 DB1 and 4.69% for FVC2004DB2.