Biometric Technologies in Recognition Systems: A Survey

Summary form only given. Biometrics refers to the automatic identification (or verification) of an individual (or a claimed identity) by using certain physical or behavioral traits associated with the person. By using biometrics it is possible to establish an identity based on `who you are¿, rather than by `what you possess¿ (e.g., an ID card) or `what you remember¿ (e.g., a password). Therefore, biometric systems use fingerprints, hand geometry, iris, retina, face, vasculature patterns, signature, gait, palmprint, or voiceprint to determine a person¿s identity. The purpose of this tutorial is two-fold: (a) to introduce the fundamentals of biometric technology from a pattern recognition and signal processing perspective by discussing some of the prominent techniques used in the field; and (b) to convey the recent advances made in this field especially in the context of security, privacy and forensics. To this end, the design of a biometric system will be discussed from the viewpoint of four commonly used biometric modalities - fingerprint, face, hand, and iris. Various algorithms that have been developed for processing these modalities will be presented. Methods to protect the biometric templates of enrolled users will also be outlined. In particular, the possibility of performing biometric matching in the cryptographic domain will be discussed. The tutorial will also introduce concepts in biometric fusion (i.e., multibiometrics) in which multiple sources of biometric information are consolidated. Finally, there will be a discussion on some of the challenges encountered by biometric systems when operating in a real-world environment and some of the methods used to address these challenges.

In recent years large number of emerging automated applications faces the need to have recognition abilities of persons using their own self biometrics, before they can access the applications services. Nowadays, Biometric recognition is used, it can be used as automatic identification or automatic verification of persons based on their physiological or behavioral characteristics. There are no perfect biometric measurements; each biometry has its advantages and limitations. Each biometry requires specific vital identity to answer the identification or verification question. The suitability of a particular biometry for a particular application depends on many factors. Hand geometry/shape is a very simple biometric technology that uses the measurements of human hand to verify the identity of the individuals. The measurements include the distance between certain mark points, shape and width of fingers and size of palm. The biometric systems that employing hand geometry become widely used since they have high public acceptance. This article aims to survey several articles found in literature about hand based biometric system, and to compare different methods of biometric recognition that based on hand geometry.

Template-Protection-Techniken stellen eine wichtige Ergänzung zu biometrischen Systemen, um das gewünschte Sicherheitsniveau zu erreichen und die Anforderungen an den Schutz der Privatsphäre zu erfüllen. Diese Techniken ermöglichen Erneuerung und Widerruf der Referenzendaten in biometrischen Systemen. In dieser Arbeit wird ein systematisches Evaluierungsframework entwickelt, das sich an die wesentlichen Kriterien und Anforderungen an biometrische Template-Protection-Verfahren festhält. Seine Anwendbarkeit wird durch die Analyse der verschiedenen Algorithmen demonstriert. Die in dieser Arbeit präsentierte Evaluierung ist grundlegend für eine vollständige Analyse. Darüber hinaus ermöglicht es einen Nachweis der Sicherheit und Einhaltung der Privatsphäre. Es schafft eine Basis für Zertifizierung und Benchmark der Template-Protection-Verfahren.

The need for fool proof authentication procedures away from traditional authentication mechanisms like passwords, security PINS has led to the advent of biometric authentication in information systems. Biometric data extracted from physiological features of a person including but not limited to fingerprints, palm prints, face or retina for purpose of verification & identification is saved as biometric templates. The inception of biometrics in access control systems has not been without its own hitches & like other systems it has its fair share of challenges. Biometric fingerprints being the most mature of all biometric spheres are the most widely adopted biometric authentication systems. Biometric systems effectiveness lies on how secure they are at preventing inadvertent disclosure of biometric templates in an information system’s archive. This however has not been the case as biometric templates have been fraudulently accessed to gain unauthorized access in identification and verification systems. In order to achieve strong and secure biometric systems, biometric systems developers need to build biometric systems that properly secure biometric templates. Several biometric template protection schemes and approaches have been proposed and used to safeguard stored biometric templates. Despite there being various biometric template protection schemes and approaches in existence, none of them has provided the most authentic, reliable, efficient and deterrent means to totally secure biometric fingerprint templates. This research sought to establish status of the current biometric template protection techniques and methods by conducting a survey and analyzing data gathered from a sample of seventy-eight (78) respondents. We will report these results and give our conclusion based on findings of the survey in this paper.

Biometric authentication systems offer a secure and convenient method of verifying the identity of individuals based on their unique physiological or behavioral traits. This paper presents a comprehensive survey of biometric authentication systems, focusing on the principles, technologies, applications, challenges, and future directions in the field. The survey covers various biometric modalities, including fingerprint recognition, iris recognition, facial recognition, keystroke dynamics, voice recognition, and gait analysis. Key topics discussed include the use of multi-modal biometric systems, continuous authentication, machine learning, and AI in biometrics, and biometric encryption. The paper also explores the implementation of biometric authentication in access control systems, financial transactions, healthcare systems, and government and law enforcement. Challenges such as security and privacy concerns, spoofing and impersonation, scalability and integration, and ethical and legal issues are addressed. Future research opportunities include improving accuracy and reliability, enhancing security and privacy, addressing societal and ethical concerns, and integrating biometric authentication with the Internet of Things (IoT).

Biometric systems have been actively emerging in various industries in the past few years and continue to provide higher-security features for access control systems. Many types of unimodal biometric systems have been developed. However, these systems are only capable of providing low- to mid-range security features. Thus, for higher-security features, the combination of two or more unimodal biometrics (multiple modalities) is required. In this paper, we propose a multimodal biometric system for person recognition using face, fingerprint, and finger vein images. Addressing this problem, we propose an efficient matching algorithm that is based on secondary calculation of the Fisher vector and uses three biometric modalities: face, fingerprint, and finger vein. The three modalities are combined and fusion is performed at the feature level. Furthermore, based on the method of feature fusion, the paper studies the fake feature which appears in the practical scene. The liveness detection is append to the system, detect the picture is real or fake based on DCT, then remove the fake picture to reduce the influence of accuracy rate, and increase the robust of system. The experimental results showed that the designed framework can achieve an excellent recognition rate and provide higher security than a unimodal biometric-based system, which are very important for a IoMT platform.

Due to peg-free system for image acquisition, it is obvious to have a motion of user’s hand. Motion activity creates the blurring effect in captured images, which leads to the false identification of a person. In such cases, image deblurring is required to restore the image. This paper proposes hand geometry- and palm texture-based person identification system with motion blur deblurring of palm images. The deblurring process may generate the ringing artifacts. The quality of the restoration of a motion blurred image is depending on the estimation of motion blur parameters, blur angle and blur length. In this paper, Radon transform and cepstral method have been used for the blur parameter estimation. Point spread function (PSF) can be constructed using blur parameters. For the deblurring of the palm images, L2/TV regularization based on augmented Lagrangian method has been used. It deblurs the image with the removal of ringing artifacts. Restored images are further used in the biometric system to analyze the robustness of the system against the motion blur. This system is tested on a database collected from 100 people. 99.5% genuine acceptance rate (GAR) is achieved for bimodal system against motion blur for discrete cosine transform (DCT)-based features. Equal error rate (EER) achieved is 1.1719.

The aim of this paper is to exploit the best possible combinations of hand geometry, palmprint and offline signatures for multimodal biometric systems by integrating the information at score level fusion. Initially, Zernike moments are extracted for each biometric trait of a person and study the identification accuracy. Subsequently, the effect of identification accuracy using score level fusion of multiple traits of a person is studied. Experiments are conducted on GPDS hand geometry database, PolyU two dimensional palmprint database and UOM offline signature database to assess the actual advantage of the fusion of multiple biometric traits performed at score level fusion, in comparison to the unimodal biometric system. The proposed methodology has shown promising results.

Automated decision tools, such as advanced energy management systems, are required to involve the electrical grid users in energy flexibility services. This paper focuses on the prediction models as a substantial part of decision strategy in advanced energy management systems and on advanced energy management systems as a tool that supports the active involvement of electrical grid users in energy flexibility services. Prediction models' desired properties are self-establishing and self-adaptation, which require new solutions in data selection, filtering, processing and model learning. Some of these properties are investigated within this paper.

This chapter will present a detailed overview of biometric systems and how they work. The system attributes, performance metrics, modalities are all discussed, alongside an analysis of attacks that exist against biometric systems. Given the limitations that exist in all biometric systems, a trend in biometric research is towards the use of multibiometric systems, which seek to overcome the issues through the application of multiple modalities, algorithms, instances or samples. These systems and the approaches that exist are presented. The chapter ends with a discussion of the efforts being made with the standardization of the domain - which has been the essential factor in bringing biometrics from a niche into the mainstream.

In the case of most of the biometric recognition systems, the type of features extracted from the biometric template depends on the biometric modality. A generalized feature representation is convenient and efficient in multimodal biometric system as the complexity involved in fusing or protecting the heterogeneous features corresponding to different biometric modalities can be avoided. The dimensionality of the features can also be reduced effectively if we can extract generalized feature vectors without compromising the matching performance. This work proposes two schemes: (i) a generalized yet efficient matching technique based on the cosine similarity of the principal component subspaces (ii) a protection scheme by fusing the feature vectors of multiple modalities in principal components domain and matching in that protected domain. The key feature of the proposed protection scheme over existing schemes is that it does not require a user specific key for ensuring the irreversibility. User specific key is used only for ensuring the revocability of the protected template. Results show that the proposed method is able to achieve a matching performance of $$98.57\%$$ for a multimodal system with face, fingerprint, and finger vein templates in the fused domain.Ragendhu, S. P. Thomas, Tony

Ambient Intelligence represents the medium with a huge number of connected heterogeneous and dynamic devices that respond to the presence of people. The development and implementation of technologies to ensure the security and reliability of such systems is the main task of many studies in this direction. One of the important technologies for the formation of a secure Ambient Intelligence is biometric systems. Biometric systems represent techniques for describing and measuring personal unique physiological and behavioral characteristics of a person and methods for applying them to automatic identification or authentication processes. In this paper, the basic principles and algorithms of a biometric identification system based on iris recognition are considered. The purpose of the research is to determine the structure of the security systems of Ambient Intelligence using biometric technologies.

With respect to generic biometric systems several different attacks have been encountered to infiltrate these [228, 418]. Recent work systematically identifies security threats against biometric systems and possible countermeasures [449] and discusses man-in-the-middle attacks and BioPhishing against a web-based biometric authentication system [606].

Using Modern Management Concepts and Tools for Developing Advanced Quality Management Systems in New Higher Education Institutions

Nowadays, embedded systems run in every setting all around the globe. Recent advances in technology have created many sophisticated applications rich with functionality we have never seen. Nonetheless, security and privacy were a common issue for these systems, whether or not sensitive data can be protected from malicious attacks. These concerns are justified on the grounds that the past of security breaches and the resulting consequences narrate horrific stories concerning embedded systems. The attacks are now evolving, becoming more complex with technological advancements. Therefore, a new way of implementing security in embedded systems must be pursued. This paper attempts to demonstrate the incorporation of security features in fingerprint biometric system in the requirements analysis phase, ensuring the same throughout the system life cycle of embedded systems based on case study. The comparison of various biometric technologies such as face, fingerprint, iris, palm print, hand geometry gait, signature, and keystroke is presented. The aim of this paper includes analyzing, decomposing and transforming the threats and counter-measures identified during the requirements analysis using the abuse case into more specific safety requirements or functions. Furthermore, we have shown that the incorporation of security features into the biometric fingerprint system by analyzing the requirements of the system and providing the main steps for the protection of the biometric system in this paper.