Biometric Systems

Because of the accelerating progress in biometrics research and the latest nation-state threats to security, this book's publication is not only timely but also much needed. This volume contains seventeen peer-reviewed chapters reporting the state of the art in biometrics research: security issues, signature verification, fingerprint identification, wrist vascular biometrics, ear detection, face detection and identification (including a new survey of face recognition), person re-identification, electrocardiogram (ECT) recognition, and several multi-modal systems. This book will be a valuable resource for graduate students, engineers, and researchers interested in understanding and investigating this important field of study

Biometrics in schools: the role of authentic and inauthentic social transactions

Biometrics have always been part of the social world, but it is only recently that we have moved from an instinctive human model of recognition to a digital one. Recent scientific developments in the field have been capitalised upon by the commercial sector and exploited in various respects by school administration systems, with biometrics becoming comparatively widespread in UK and US schools. This brings both advantages and disadvantages as biometrics begin to change the fundamental relationship between institutions and the children in their care. This paper discusses the current state of research in terms of biometrics and social identity, the impact of commercial pressures to adopt biometric systems, and the growing relationship with data privacy issues. It analyses potential problems surrounding unproblematic adoption, and discusses how this might inform future data privacy policies. Additionally, in the paper, I identify three key social issues relating to biometric use in schools, and offer a theory of social exchange, building on the work of Homans. This includes a classification of authentic versus inauthentic transations, in the democratic sense. Finally, the paper identifies biometrics as an area of social (and legal) risk for the future

Machine Learning for Biometrics

Biometrics aims at reliable and robust identification of humans from their personal traits, mainly for security and authentication purposes, but also for identifying and tracking the users of smarter applications. Frequently considered modalities are fingerprint, face, iris, palmprint and voice, but there are many other possible biometrics, including gait, ear image, retina, DNA, and even behaviours. This chapter presents a survey of machine learning methods used for biometrics applications, and identifies relevant research issues. We focus on three areas of interest: offline methods for biometric template construction and recognition, information fusion methods for integrating multiple biometrics to obtain robust results, and methods for dealing with temporal information. By introducing exemplary and influential machine learning approaches in the context of specific biometrics applications, we hope to provide the reader with the means to create novel machine learning solutions to challenging biometrics problems

TOWARDS AN OPEN BIOMETRIC ONTOLOGY

Over the last decade we faced a great number of publications in the field of biometrics. Many new biometric methods, techniques, models, metrics and characteristics were proposed. Due to this explosion of research, scientific and professional papers certain inconsistencies in terminology. What some authors call a biometric method, others call model, system or even characteristic. There wasn\u27t enough effort in creating a unique systematization and categorization which would approach the stated issues and open new areas of research. We argue that it is possible to approach biometrics in a narrower and in a broader perspective. We observed biometrics in the narrower perspecive and created a unique framework for the systematization and categorization of biometric methods, models, characteristics and patterns based on a general biometric system. This systematization is a fundamental step forward towards the creation of an open biometrics ontology

Vision-based techniques for gait recognition

Global security concerns have raised a proliferation of video surveillance devices. Intelligent surveillance systems seek to discover possible threats automatically and raise alerts. Being able to identify the surveyed object can help determine its threat level. The current generation of devices provide digital video data to be analysed for time varying features to assist in the identification process. Commonly, people queue up to access a facility and approach a video camera in full frontal view. In this environment, a variety of biometrics are available - for example, gait which includes temporal features like stride period. Gait can be measured unobtrusively at a distance. The video data will also include face features, which are short-range biometrics. In this way, one can combine biometrics naturally using one set of data. In this paper we survey current techniques of gait recognition and modelling with the environment in which the research was conducted. We also discuss in detail the issues arising from deriving gait data, such as perspective and occlusion effects, together with the associated computer vision challenges of reliable tracking of human movement. Then, after highlighting these issues and challenges related to gait processing, we proceed to discuss the frameworks combining gait with other biometrics. We then provide motivations for a novel paradigm in biometrics-based human recognition, i.e. the use of the fronto-normal view of gait as a far-range biometrics combined with biometrics operating at a near distance

Biometrics for internet‐of‐things security: A review

The large number of Internet‐of‐Things (IoT) devices that need interaction between smart devices and consumers makes security critical to an IoT environment. Biometrics offers an interesting window of opportunity to improve the usability and security of IoT and can play a significant role in securing a wide range of emerging IoT devices to address security challenges. The purpose of this review is to provide a comprehensive survey on the current biometrics research in IoT security, especially focusing on two important aspects, authentication and encryption. Regarding authentication, contemporary biometric‐based authentication systems for IoT are discussed and classified based on different biometric traits and the number of biometric traits employed in the system. As for encryption, biometric‐cryptographic systems, which integrate biometrics with cryptography and take advantage of both to provide enhanced security for IoT, are thoroughly reviewed and discussed. Moreover, challenges arising from applying biometrics to IoT and potential solutions are identified and analyzed. With an insight into the state‐of‐the‐art research in biometrics for IoT security, this review paper helps advance the study in the field and assists researchers in gaining a good understanding of forward‐looking issues and future research directions

"Are we getting the biometric bioethics right?" - the use of biometrics within the healthcare system in Malawi.

Biometrics is the science of establishing the identity of an individual based on their physical attributes. Ethical concerns surrounding the appropriate use of biometrics have been raised, especially in resource-poor settings. A qualitative investigation was conducted to explore biometrics clients (n = 14), implementers (n = 12) and policy makers as well as bioethicists (n = 4) perceptions of the ethical aspects of implementing biometrics within the healthcare system in Malawi. Informed use, privacy and confidentiality as well as perceptions of benefits and harms were identified as major issues in the application of biometrics. Implementation of biometrics within the healthcare system in Malawi poses a range of potential ethical issues and practical challenges that impact on equitable uptake. There is a need for more research to explore the benefits and harms of biometrics in practice. Improved community engagement and sensitization should be a required component of biometrics introduction in Malawi