Biometric Authentication Methods Research Articles

Vulnerabilities in One Time Passwords and Protection Method Using Secret Key and Biometric Hash Code

In the present era, conducting financial transactions online is both simple and widely embraced for its convenience. However, engaging in internet-based financial transactions exposes individuals to potential threats like password attacks, malware, phishing, and other illicit activities. Recognizing these risks, many banks have enhanced security measures by incorporating One-Time Password (OTP) authentication alongside traditional login credentials. Despite these improvements, security issues persist in online transactions. To mitigate such concerns, OTPs can be delivered via SMS to the account owner's mobile number. Even with heightened security, internet banking remains susceptible to various attacks, including online phishing, Man-in-the-Middle attacks, SQL injection, and brute force attacks. To address these challenges, this proposed model introduces a Biometric mobile OTP-based transaction authentication method.

A framework for security improvement on usage of mobile money application based on iris biometric authentication method

ABSTRACT Offering transactions through mobile devices has many advantages, such as cashless payments, lower transaction costs, and provide employment opportunities. However, it introduces access security challenges that must be dealt with, which may allow unauthorized access, resulting in theft. This work proposes a framework to improve security on the usage of Mobile Money Services (MMS) by using two-factor authentication (2FA) of PIN and iris biometric authentication method (IRBAM). The rapid application development (RAD) approach was used to develop mobile money applications based on the proposed framework. The proposed framework will improve the security of accessing MMS.

Analysis of Biometric-Based Cryptographic Key Exchange Protocols—BAKE and BRAKE

Biometric authentication methods offer high-quality mechanisms to confirm the identity of individuals in security systems commonly used in the modern world, such as physical access control, online banking, or mobile device unlocking. They also find their application in cryptographic solutions, which allow the biometrically authenticated exchange of cryptographic keys between users and services on the internet, despite the fuzziness of biometric data. Such solutions are BAKE (biometrics-authenticated key exchange) and BRAKE (biometric-resilient authenticated key exchange) protocols, upon which our work is based. However, the direct application of fuzzy biometrics in cryptography, which relies heavily on the accuracy of single-bit secret values, is not trivial. Therefore, this paper is devoted to analyzing the security of this idea and the feasibility of implementing biometric AKE (authenticated key exchange) protocols, with an emphasis on the BRAKE protocol. As the results of our analysis, we discuss BRAKE’s limitations and vulnerabilities, which need to be appropriately addressed to implement the protocol in modern systems.

Data Collection Module for a Centralized Electronic Health Records System

Electronic Health Records (EHRs) play a crucial role in modern healthcare, enhancing quality, safety, efficiency, and research capabilities. However, in Nigeria the full acceptance of such modern ways of managing healthcare delivery is marred with various challenges such as infrastructure, funding, technical expertise, and regulatory issues. This paper presents a proposed conceptual framework of a Data Collection Module for a Centralized EHR System in Nigeria, aimed at addressing data accessibility challenges faced by healthcare facilities for patients registering at their facilities. The module utilizes National Identification Numbers (NINs), barcodes, and biometric identification methods to collect and secure patient demographic data. It incorporates a web application, biometric software, and barcode/QR code software to ensure efficient data collection and verification. Our study demonstrates the feasibility and effectiveness of employing biometric identification techniques in data collection modules, offering enhanced accuracy, reliability, security, and usability of patient data in a developing healthcare system like Nigeria.The proposed module has not been tested in a real-world environment, so more study is required to determine its viability, scalability, and effect on the standard and results of healthcare.

Towards Secure Identification: A Comparative Analysis of Biometric Authentication Techniques

This paper provides an overview and analysis of existing biometric authentication methods. Biometric authentication enhances the security of traditional authentication methods by utilizing unique biological characteristics of individuals, such as fingerprints, facial features, or iris patterns, to verify identity. However, implementing biometric authentication may involve initial setup costs for service providers due to the need for specialized hardware and software. Additionally, users may experience some initial inconvenience during the enrollment process to register their biometric data. This paper presents a comparative analysis of the usability of biometric authentication techniques. Initially, a survey of existing work is conducted by comparing techniques, algorithms, and metrics used in research. Later the challenges of the distinct types of authentication techniques are discussed, and their problems are discovered. Subsequently, the findings of a quantitative study based on a are presented, aimed at assessing the usability of those techniques. The findings indicate that authentic biometric techniques are perceived as usable.

Wide Field of View Under-Panel Optical Lens Design for Fingerprint Recognition of Smartphone.

Fingerprint recognition is a widely used biometric authentication method in LED-backlight smartphones. Due to the increasing demand for full-screen smartphones, under-display fingerprint recognition has become a popular trend. In this paper, we propose a design of an optical fingerprint recognition lens for under-display smartphones. The lens is composed of three plastic aspheric lenses, with an effective focal length (EFL) of 0.61 mm, a field of view (FOV) of 126°, and a total track length (TTL) of 2.54 mm. The image quality of the lens meets the target specifications, with MTF over 80% in the center FOV and over 70% in the 0.7 FOV, distortion less than 8% at an image height of 1.0 mm, and relative illumination (RI) greater than 25% at an image height of 1.0 mm. The lens also meets the current industry standards in terms of tolerance sensitivity and Monte Carlo analysis.

Risk Analysis Research on SMS Verification Code and Biometric Recognition Technology

This paper delves into the ongoing transformation in the domain of digital identity security. It specifically focuses on the paradigm shift from traditional methods of authentication, such as passwords and text message verification codes, towards the use of biometric recognition technology. By scrutinizing the inherent weaknesses linked with the utilization of text message verification codes, the paper underlines the demand for more trustworthy and secure solutions for authentication. Following this, biometric authentication is thoroughly examined, with a highlight on its unique features, the convenience it provides to users, and its capacity for ongoing verification. The discussion extends to practical applications of biometrics in a variety of sectors, including healthcare and high-security workplaces, as well as in situations where employing text message verification is unsuitable. A focal point of the discussion is multi-modal biometric authentication. While acknowledging the potential hurdles and future possibilities tied to the adoption of biometric technology, the paper offers an objective perspective. The overall intent of this research is to furnish insights that will enable informed decision-making regarding the deployment and improvement of digital identity verification methods across a wide range of industries.

Deep learning-based photoplethysmography biometric authentication for continuous user verification

Biometric authentication methods have gained prominence as secure and convenient alternatives to traditional passwords and PINs. In this paper, we propose a novel approach for biometric authentication using photoplethysmography (PPG) signals and deep learning techniques. PPG is a non-invasive method that measures variations in blood volume within microvascular tissue beds, and it is typically used for monitoring heart rate and oxygen saturation. Our research leverages the unique characteristics of PPG signals to develop a robust and continuous user verification system. The primary goal of our study is to explore the feasibility and effectiveness of PPG-based biometric authentication, enabling a seamless and secure means of confirming the identity of individuals. We use a diverse dataset of PPG signals from various individuals, ensuring that it encompasses differences in skin tone, age, and other variables that can influence PPG signal characteristics. The collected data undergoes careful preprocessing, including noise removal, baseline correction, and heartbeat segmentation. For the core of our authentication system, we design and train a multiscale feature fusion deep learning (MFFD) model. This model, utilizing a Convolutional Neural Network (CNN) architecture, takes as input the relevant features extracted from PPG signals and learns to differentiate between individuals based on their unique PPG patterns. In this study, the input is constructed by gradually incorporating various features, beginning with a single PPG signal. In this study, the CNN model was trained independently, followed by the implementation of score fusion techniques. Our evaluation demonstrates the effectiveness of the PPG-based biometric authentication system, achieving high accuracy while addressing key security concerns. We consider false acceptance rate (FAR) and false rejection rate (FRR) to assess the system's performance. The model achieves the Accuracy of 99.5 % on BIDMC, 98.6 % on MIMIC, 99.2 % on CapnoBase dataset.

Iris-Based Biometric Identification Using a Combination of the Right - Left Iris Statistical Features

A combination between the information extracted for both right iris and left iris could increase the efficacy of the biometric recognition systems. In this paper, we propose a biometric identification method based on density of image patterns extracted from human iris images and the combination and comparison of the right iris and the left iris characteristics. The density of the patters approach for processed images can be a new biometric feature used to implement a biometric recognition system with high performance when a small feature dimension is used. In this way, we can maximize the retention of the effective biometric information. The experiments were conducted on the MMU Iris Database containing 225 images of the left eye and 225 images of the right eye. Two morphological Top-hat and Hit or Miss transforms were implemented to find out the particular pattern of pixels. They allow for the enhancement of detail in images. Then, a statistical feature extraction technique is employed to derive the density of the patterns in morphological transformed images. To assess the density of the patterns differences between the right and left iris data groups, the Pearson’s correlation coefficient (PCC) is computed. We reported very good results with a PCC of 0.6164 (strong and positive correlation) for Top-hat morphological operation whilst the Hit or Miss transform returns a PCC of 0.0127 so there is no relationship between the density of the patterns in the right and left irises.

Research Paper on Fingerprint Identification

Fingerprint identification is one of the most popular and reliable personal biometric identification methods. This paper describes an on-line fingerprint identification system consisting of image acquisition, edge detection, thinning, feature extractor, and classifier. The preprocessing part includes steps to acquire binarized and skeletonized ridges, which are needed for feature point extraction. Feature points (minutia) such as endpoints, bifurcations, and core points are then extracted, followed by false minutia elimination. Human fingerprints are rich in details called minutiae, which can be used as identification marks for fingerprint verification. The goal of this project is to develop a complete system for fingerprint identification.

Express method of biometric person authentication based on one cycle of the ECG signal

The article is devoted to an express method of biometric authentication of a person based on an electrocardiogram (ECG). The method is characterized by high accuracy (efficiency) of authentication of a person based on only one cycle of its ECG. Such characteristics as Accuracy, Balanced Accuracy and F1-score on average are not lower than 96.1% for such binary classifiers as k-Nearest Neighbors, Linear SVM, Decision Tree, Random Forest, Multilayer Perceptron, Adaptive Boosting, Naive Bayes and Statistical Interval Classifier. The research utilized the Combined Measurement of ECG, Breathing, and Seismocardiograms database, which features data from 20 healthy people. A method of constructing confidence intervals for ECG cycles has been developed, which is based on the rhythm-adaptive statistical estimation of the mathematical expectation and the standard deviation of the ECG signal. The method of constructing confidence intervals is based on the functioning of the Statistical Interval Classifier in the system of biometric authentication of a person. The Statistical Interval Classifier has the lowest time computational complexity among the 8 studied classifiers, which justifies its use in portable biometric authentication systems that have negligible computing resources.

“Risky or Trustworthy?”: User Behavior towards Biometric Authentication Method

Smartphones as a means of communication are not only used to send and receive messages and make phone calls. Today's smartphones are also intended to store personal data and sensitive information hence it is vulnerable to be illegally accessed by others. Fingerprint as a biometric lock screen for smartphones can be trusted to ensure the security and privacy of smartphone users. A fingerprint is closely related to a user's identity. When using fingerprints, users provide their personal biometric pattern, unknowingly giving their privacy and making them vulnerable to unauthorized use of their biometric pattern. This study is designed to reveal the factors that influence users when using fingerprints as a smartphone lock, using eight variables adapted from previous research. The data analysis used is Partial Least Squares (PLS) analysis. The results of this study suggest that trust, attitudes, and perceived risk are the factors that influence users when using their fingerprint as a smartphone lock.

Ethical Aspects of Biometric Identification

The term biometrics derives from Greek (bio=life and metrics=measure) and implies the measurement of biological signs. Biometrics is the science of recognizing people based on their physical, behavioral, and physiological attributes, such as fingerprint, face scan, iris, retina, and voice. The present paper aims to develop a study on biometric identification. The major objective of the study is to conduct a survey among the Romanian population on the importance and knowledge of biometric identification methods. This objective was achieved by assessing the knowledge held by the general population of Romania regarding biometric indicators and the degree of adaptability and openness of citizens related to the widest possible implementation of biometrics. The study was based on conducting a quantitative analysis using a questionnaire. Due to the high degree of accessibility, the online environment was chosen as a method of application, distribution being made through social networks. A biometric template digitizes the human body, it has been argued that the collection of biometric identifiers not only interferes with the privacy and right to protection of a person's data, but also with the integrity of an individual's body. In conclusion, the creation and storage of a unique biometric template must be seen in relation to the purpose of the operation. The protection of citizens from criminal activities is a primary obligation of the state. However, it must be exercised with due respect for a number of fundamental ethical values and in the light of modern human rights law.

The Role of Artificial Intelligence in Diagnosing Heart Disease in Humans: A Review

The electrical activity of the heart and the electrocardiogram (ECG) signal are fundamentally related. In the study that has been published, the ECG signal has been examined and used for a number of applications. The monitoring of heart rate and the analysis of heart rhythm patterns, the detection and diagnosis of cardiac diseases, the identification of emotional states, and the use of biometric identification methods are a few examples of applications in the field. Several various phases may be involved in the analysis of electrocardiogram (ECG) data, depending on the type of study being done. Preprocessing, feature extraction, feature selection, feature modification, and classification are frequently included in these stages. Every stage must be finished in order for the analysis to go smoothly. Additionally, accurate success measures and the creation of an acceptable ECG signal database are prerequisites for the analysis of electrocardiogram (ECG) signals. Identification and diagnosis of various cardiac illnesses depend heavily on the ECG segmentation and feature extraction procedure. Electrocardiogram (ECG) signals are frequently obtained for a variety of purposes, including the diagnosis of cardiovascular conditions, the identification of arrhythmias, the provision of physiological feedback, the detection of sleep apnea, routine patient monitoring, the prediction of sudden cardiac arrest, and the creation of systems for identifying vital signs, emotional states, and physical activities. The ECG has been widely used for the diagnosis and prognosis of a variety of heart diseases. Currently, a range of cardiac diseases can be accurately identified by computerized automated reports, which can then generate an automated report. This academic paper aims to provide an overview of the most important problems associated with using deep learning and machine learning to diagnose diseases based on electrocardiography, as well as a review of research on these techniques and methods and a discussion of the major data sets used by researchers.

Mitigating Risks in the Cloud-Based Metaverse Access Control Strategies and Techniques

The advent of the metaverse has revolutionized virtual interactions and navigation, introducing intricate access control challenges. This paper addresses the need for effective access control models in the cloud-based metaverse. It explores its distinct characteristics, including its dynamic nature, diverse user base, and shared spaces, highlighting privacy concerns and legal implications. The paper analyzes access control principles specific to the cloud-based metaverse, emphasizing least privilege, separation of duties, RBAC, defense-in-depth, and auditability/accountability. It delves into identity verification and authorization methods, such as biometrics, multi-factor authentication, and role-based/attribute-based authorization. Advanced access control technologies for the cloud-based metaverse are examined, including SSO solutions, blockchain-based access control, ABAC, adaptive access control, and VMI for isolation. Risk mitigation strategies encompass IDS/IPS, SIEM, and user education programs.

Using biometric data to protect information

Objective. An urgent task is to evaluate the system for protecting access to information while minimizing errors, based on the use of human biometric data. It is necessary to evaluate and compare methods and solutions of biometric authentication, and the possibility of combining them.Method. The method for assessing and comparing biometric authentication methods and solutions is based on practical experience and regulatory and technical documentation on the use of biometric data for information security purposes. It is necessary to complicate the possibility of unauthorized access to information. At the same time, improving the system should not worsen the comfort of a legitimate user when trying to access. The remaining tasks are to reduce entry time and simplify the system.Result. An assessment of biometric authentication methods and solutions was carried out and a solution was proposed for the development of biometric authentication systems to protect against unauthorized access, the key criteria in which were the complexity of hacking, user comfort, login time and simplification of the system.Conclusion. The optimal solution in the development of biometric authentication systems would be to use multi-factor authentication using dynamic parameters of the access subject. A modern biometric authentication system should be installed taking into account the level of security required at the time.

Developing a Remote Access System by Interfacing ESP32 Microcontroller with 4X4 Keypad

Remote access with a microcontroller refers to the capability to control and communicate with a system based on a microcontroller from a remote location. The paper discusses the creation of a reliable remote access and control system using the ESP32 microcontroller and a 4x4 keypad. This system blends ease of use with robust security measures. With the increasing demand for secure access control solutions, this system makes a significant contribution to the realm of IoT-based authentication systems. Future endeavors may encompass scalability testing, integration with other biometric authentication methods, and additional refinements to expand its applicability

The main features of the public key infrastructure

Trust is the basis of any communication, whether it is built in the physical world or in the digital environment. Establishing trust in the physical world does not pose any particular challenges because communication subjects can identify each other through biometric features, identity card or other identification documents. In the digital environment, a number of difficulties arise for the identification and authentication procedure. The communicating parties do not meet face-to-face and can be at a significant distance from each other. As a result, they cannot identify uniquely and verify each other's identity using the identity verification methods used in the material world. To ensure the security of electronic communications, it is necessary for communication systems to be equipped with technical means of information protection and an additional mechanism that will contribute to the establishment of trust between the parties to the communication. The Public Key Infrastructure is used to solve problems related to trust, authentication, identity, and security on a network. A digital certificate is a fundamental element for establishing trust in the digital world. It plays a crucial role in ensuring security and identification on the Internet and when working with electronic resources. The Public Key Infrastructure is a trusted system used to ensure the security and privacy of information across networks and platforms. This system is based on public key cryptography. It implements the management of public keys and digital certificates of various entities, such as companies, corporations, organizations, individuals, websites, servers, etc. The Public Key Infrastructure is widely deployed in government portals and systems. It is used in the electronic government system to guarantee the transparency of the provision of electronic services and to ensure the security of communication links between authorities and society. The Public Key Infrastructure represents a multifaceted structure that includes a set of standards, technologies, and procedures for managing, storing, and distributing keys and digital certificates. A certificate authority is a key component of a public key infrastructure and is an independent third party that manages digital certificates. Various technical and cryptographic means of information security are used in the Public Key Infrastructure, such as digital signatures, encryption, hash functions, hardware security modules, key management software, etc. The main purpose of this article is to analyze the main features and aspects of public key infrastructure.

Deep learning-based intelligent system for fingerprint identification using decision-based median filter

Fingerprint recognition has emerged as one of the most reliable biometric authentication methods, owing to its uniqueness and permanence. However, the security and confidentiality of the user’s data are key considerations in modern biometric systems. In this study, we describe an intelligent computational technique for automatically validating fingerprints for identification and verification purposes. The feature vector is created by fusing Gabor filtering features with deep learning techniques like the faster region-based convolutional neural network (Faster R-CNN). This study uses linear and decision-based median filtering (DBMF) techniques to minimize visual impulse noise. Faster-R-CNN with DBMF was applied to the feature vectors to reduce overfitting problems while improving classification precision and reliability. For fingerprint matching, the Euclidean distance between the associated Harris-SURF feature vectors of two feature points is used to measure feature-matching similarity between two fingerprint images. Furthermore, for fine-tuned matching an iterative technique known as RANSAC (Random Sample Consensus) is used. The experimental results collected from the public-domain fingerprint databases FVC-2002 DB1 and FVC-2000 DB1 show that the proposed design is viable and performs well with an accuracy of 99.43%, MSE value of 43.321%, and an execution time of 3.102 ms which was more exact than existing models.

Tongue prints- Unique as well as potential forensic tool for biometric authentication

Forensic odontology proves to be an important branch of science when it comes to solve various criminal cases as well as in person identification by providing dental expertise in the court of law so that proper justice can be delivered. Tongue is an important vital organ of human body which is protected from outer environment as it is well encased within the oral cavity. Tongue has very unique features which differs from individual to individual, even in identical twins. For this reason, tongue prints can be used nowadays as a method of biometric authentication in Forensic Odontology. It also aids in identification of person as tongue exhibits sexual dimorphism. As a result of all this, tongue prints has emerged as a promising forensic tool nowadays.