Ai And Deep Learning In Biometric Security

Author : Gaurav Jaswal
Publisher : CRC Press
ISBN 13 : 1000291626
Total Pages : 378 pages
Book Rating : 4.29/5 ( download)

DOWNLOAD NOW!

Download or read book AI and Deep Learning in Biometric Security written by Gaurav Jaswal and published by CRC Press. This book was released on 2021-03-21 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.

Author : KC Santosh
Publisher : Springer Nature
ISBN 13 : 9811939357
Total Pages : 71 pages
Book Rating : 4.58/5 ( download)

DOWNLOAD NOW!

Download or read book AI, Ethical Issues and Explainability—Applied Biometrics written by KC Santosh and published by Springer Nature. This book was released on 2022-08-24 with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI has contributed a lot and biometrics is no exception. To make AI solutions commercialized/fully functional, one requires trustworthy and explainable AI (XAI) solutions while respecting ethical issues. Within the scope of biometrics, the book aims at both revisiting ethical AI principles by taking into account state-of-the-art AI-guided tools and their responsibilities i.e., responsible AI. With this, the long-term goal is to connect with how we can enhance research communities that effectively integrate computational expertise (with both explainability and ethical issues). It helps combat complex and elusive global security challenges that address our national concern in understanding and disrupting the illicit economy.

Author : Mayank Vatsa
Publisher : CRC Press
ISBN 13 : 1351264982
Total Pages : 254 pages
Book Rating : 4.83/5 ( download)

DOWNLOAD NOW!

Download or read book Deep Learning in Biometrics written by Mayank Vatsa and published by CRC Press. This book was released on 2018-03-05 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning is now synonymous with applied machine learning. Many technology giants (e.g. Google, Microsoft, Apple, IBM) as well as start-ups are focusing on deep learning-based techniques for data analytics and artificial intelligence. This technology applies quite strongly to biometrics. This book covers topics in deep learning, namely convolutional neural networks, deep belief network and stacked autoencoders. The focus is also on the application of these techniques to various biometric modalities: face, iris, palmprint, and fingerprints, while examining the future trends in deep learning and biometric research. Contains chapters written by authors who are leading researchers in biometrics. Presents a comprehensive overview on the internal mechanisms of deep learning. Discusses the latest developments in biometric research. Examines future trends in deep learning and biometric research. Provides extensive references at the end of each chapter to enhance further study.

Author : Bir Bhanu
Publisher : Springer
ISBN 13 : 3319616579
Total Pages : 312 pages
Book Rating : 4.75/5 ( download)

DOWNLOAD NOW!

Download or read book Deep Learning for Biometrics written by Bir Bhanu and published by Springer. This book was released on 2017-08-01 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris, fingerprint, and vascular biometric systems, in addition to surveillance systems that use soft biometrics. Issues of biometrics security are also examined. Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities; revisits deep learning for face biometrics, offering insights from neuroimaging, and provides comparison with popular CNN-based architectures for face recognition; examines deep learning for state-of-the-art latent fingerprint and finger-vein recognition, as well as iris recognition; discusses deep learning for soft biometrics, including approaches for gesture-based identification, gender classification, and tattoo recognition; investigates deep learning for biometrics security, covering biometrics template protection methods, and liveness detection to protect against fake biometrics samples; presents contributions from a global selection of pre-eminent experts in the field representing academia, industry and government laboratories. Providing both an accessible introduction to the practical applications of deep learning in biometrics, and a comprehensive coverage of the entire spectrum of biometric modalities, this authoritative volume will be of great interest to all researchers, practitioners and students involved in related areas of computer vision, pattern recognition and machine learning.

Author : Partha Pratim Sarangi
Publisher : Academic Press
ISBN 13 : 0323903398
Total Pages : 266 pages
Book Rating : 4.94/5 ( download)

DOWNLOAD NOW!

Download or read book Machine Learning for Biometrics written by Partha Pratim Sarangi and published by Academic Press. This book was released on 2022-01-21 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning for Biometrics: Concepts, Algorithms and Applications highlights the fundamental concepts of machine learning, processing and analyzing data from biometrics and provides a review of intelligent and cognitive learning tools which can be adopted in this direction. Each chapter of the volume is supported by real-life case studies, illustrative examples and video demonstrations. The book elucidates various biometric concepts, algorithms and applications with machine intelligence solutions, providing guidance on best practices for new technologies such as e-health solutions, Data science, Cloud computing, and Internet of Things, etc. In each section, different machine learning concepts and algorithms are used, such as different object detection techniques, image enhancement techniques, both global and local feature extraction techniques, and classifiers those are commonly used data science techniques. These biometrics techniques can be used as tools in Cloud computing, Mobile computing, IOT based applications, and e-health care systems for secure login, device access control, personal recognition and surveillance. Covers different machine intelligence concepts, algorithms and applications in the field of cybersecurity, e-health monitoring, secure cloud computing and secure IOT based operations Explores advanced approaches to improve recognition performance of biometric systems with the use of recent machine intelligence techniques Introduces detection or segmentation techniques to detect biometric characteristics from the background in the input sample

Author : Ahmed A. Abd El-Latif
Publisher : IET
ISBN 13 : 1839535474
Total Pages : 289 pages
Book Rating : 4.75/5 ( download)

DOWNLOAD NOW!

Download or read book Artificial Intelligence for Biometrics and Cybersecurity written by Ahmed A. Abd El-Latif and published by IET. This book was released on 2023-11-07 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: The integration of new technologies is resulting in an increased demand for security and authentication in all types of data communications. Cybersecurity is the protection of networks and systems from theft. Biometric technologies use unique traits of particular parts of the body such facial recognition, iris, fingerprints and voice to identify individuals' physical and behavioural characteristics. Although there are many challenges associated with extracting, storing and processing such data, biometric and cybersecurity technologies along with artificial intelligence (AI) are offering new approaches to verification procedures and mitigating security risks. This book presents cutting-edge research on the use of AI for biometrics and cybersecurity including machine and deep learning architectures, emerging applications and ethical and legal concerns. Topics include federated learning for enhanced cybersecurity; artificial intelligence-based biometric authentication using ECG signal; deep learning for email phishing detection methods; biometrics for secured IoT systems; intelligent authentication using graphical one-time-passwords; and AI in social cybersecurity. Artificial Intelligence for Biometrics and Cybersecurity: Technology and applications is aimed at artificial intelligence, biometrics and cybersecurity experts, industry and academic researchers, network security engineers, cybersecurity professionals, and advanced students and newcomers to the field interested in the newest advancements in artificial intelligence for cybersecurity and biometrics.

Author : Mark Stamp
Publisher : Springer Nature
ISBN 13 : 3030970876
Total Pages : 388 pages
Book Rating : 4.71/5 ( download)

DOWNLOAD NOW!

Download or read book Artificial Intelligence for Cybersecurity written by Mark Stamp and published by Springer Nature. This book was released on 2022-07-15 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.

Author : Kisku, Dakshina Ranjan
Publisher : IGI Global
ISBN 13 : 152257526X
Total Pages : 300 pages
Book Rating : 4.69/5 ( download)

DOWNLOAD NOW!

Download or read book Design and Implementation of Healthcare Biometric Systems written by Kisku, Dakshina Ranjan and published by IGI Global. This book was released on 2019-01-11 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Healthcare sectors often deal with a large amount of data related to patients’ care and hospital workforce management. Mistakes occur, and the impending results are disastrous for individuals’ personal identity information. However, an innovative and reliable way to safeguard the identity of individuals and provide protection of medical records from criminals is already in effect. Design and Implementation of Healthcare Biometric Systems provides innovative insights into medical identity theft and the benefits behind biometrics technologies that could be offered to protect medical records from hackers and malicious users. The content within this publication represents the work of ASD screening systems, healthcare management, and patient rehabilitation. It is designed for educators, researchers, faculty members, industry practitioners, graduate students, and professionals working with healthcare services and covers topics centered on understanding the practical essence of next-generation healthcare biometrics systems and future research directions.

Author : Sun Yuan Kung
Publisher : Prentice Hall
ISBN 13 :
Total Pages : 504 pages
Book Rating : 4.74/5 ( download)

DOWNLOAD NOW!

Download or read book Biometric Authentication written by Sun Yuan Kung and published by Prentice Hall. This book was released on 2005 with total page 504 pages. Available in PDF, EPUB and Kindle. Book excerpt: A breakthrough approach to improving biometrics performanceConstructing robust information processing systems for face and voice recognitionSupporting high-performance data fusion in multimodal systemsAlgorithms, implementation techniques, and application examples Machine learning: driving significant improvements in biometric performance As they improve, biometric authentication systems are becoming increasingly indispensable for protecting life and property. This book introduces powerful machine learning techniques that significantly improve biometric performance in a broad spectrum of application domains. Three leading researchers bridge the gap between research, design, and deployment, introducing key algorithms as well as practical implementation techniques. They demonstrate how to construct robust information processing systems for biometric authentication in both face and voice recognition systems, and to support data fusion in multimodal systems. Coverage includes: How machine learning approaches differ from conventional template matchingTheoretical pillars of machine learning for complex pattern recognition and classificationExpectation-maximization (EM) algorithms and support vector machines (SVM)Multi-layer learning models and back-propagation (BP) algorithmsProbabilistic decision-based neural networks (PDNNs) for face biometricsFlexible structural frameworks for incorporating machine learning subsystems in biometric applicationsHierarchical mixture of experts and inter-class learning strategies based on class-based modular networksMulti-cue data fusion techniques that integrate face and voice recognitionApplication case studies

Author : Fei Hu
Publisher : CRC Press
ISBN 13 : 1000878899
Total Pages : 420 pages
Book Rating : 4.99/5 ( download)

DOWNLOAD NOW!

Download or read book AI, Machine Learning and Deep Learning written by Fei Hu and published by CRC Press. This book was released on 2023-06-05 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today, Artificial Intelligence (AI) and Machine Learning/ Deep Learning (ML/DL) have become the hottest areas in information technology. In our society, many intelligent devices rely on AI/ML/DL algorithms/tools for smart operations. Although AI/ML/DL algorithms and tools have been used in many internet applications and electronic devices, they are also vulnerable to various attacks and threats. AI parameters may be distorted by the internal attacker; the DL input samples may be polluted by adversaries; the ML model may be misled by changing the classification boundary, among many other attacks and threats. Such attacks can make AI products dangerous to use. While this discussion focuses on security issues in AI/ML/DL-based systems (i.e., securing the intelligent systems themselves), AI/ML/DL models and algorithms can actually also be used for cyber security (i.e., the use of AI to achieve security). Since AI/ML/DL security is a newly emergent field, many researchers and industry professionals cannot yet obtain a detailed, comprehensive understanding of this area. This book aims to provide a complete picture of the challenges and solutions to related security issues in various applications. It explains how different attacks can occur in advanced AI tools and the challenges of overcoming those attacks. Then, the book describes many sets of promising solutions to achieve AI security and privacy. The features of this book have seven aspects: This is the first book to explain various practical attacks and countermeasures to AI systems Both quantitative math models and practical security implementations are provided It covers both "securing the AI system itself" and "using AI to achieve security" It covers all the advanced AI attacks and threats with detailed attack models It provides multiple solution spaces to the security and privacy issues in AI tools The differences among ML and DL security and privacy issues are explained Many practical security applications are covered