Biometric Security and Privacy, Softcover reprint of the original 1st ed. 2017 Opportunities & Challenges in The Big Data Era Signal Processing for Security Technologies Series

This book highlights recent research advances on biometrics using new methods such as deep learning, nonlinear graph embedding, fuzzy approaches, and ensemble learning. Included are special biometric technologies related to privacy and security issues, such as cancellable biometrics and soft biometrics. The book also focuses on several emerging topics such as big data issues, internet of things, medical biometrics, healthcare, and robot-human interactions. The authors show how these new applications have triggered a number of new biometric approaches. They show, as an example, how fuzzy extractor has become a useful tool for key generation in biometric banking, and vein/heart rates from medical records can also be used to identify patients. The contributors cover the topics, their methods, and their applications in depth.

Richard Jiang is a Lecturer in the department of Computer Science and Digital Technologies, Northumbria University, Newcastle upon Tyne, UK. He received his PhD in Computer Science from Queen’s University Belfast, Belfast, UK, in July 2008. After his PhD study, he has been working in Brunel Univ., Loughborough Univ., Swansea Univ., Univ. of Bath and Univ. of Sheffield. His research interests mainly reside in the fields of Artificial Intelligence, Man-Machine Interaction, Visual Forensics, and Biomedical Image Analysis. His research has been funded by EPSRC, BBSRC, TSB, EU FP, and industry funds, and he has authored and coauthored more than 40 publications.

Danny Crookes was appointed to the Chair of Computer Engineering in 1993 at Queens University Belfast, and was Head of Computer Science from 1993 to 2002. He is Director of Research for Speech, Image and Vision Systems at the Institute for Electronics, Communications and Information Technology (ECIT) at Queens University Belfast. His current research interests include the use of novel architectures (especially GPUs) for high-performance image processing. He has applied expertise in language design, optimizing compilers and software generators, plus software tools for hardware description and architecture generation, to the goal of developing high level software tools to enable rapid development of real-time video processing systems. He is currently involved in projects in automatic shoeprint recognition (ESPRC), speech separation and enhancement (EPSRC) and processing of 4D confocal microscopy imagery (sponsored by INI and Andor Technologies). He has published over 200 scientific papers in journals and international conferences, and has presented tutorials on parallel image processing at several international conferences.

Ahmed Bouridane received the M.Phil. degree in electrical engineering (VLSI design for signal processing) from the University of Newcastle-Upon-