Multimodal Biometric Systems: Security and Applications
- Length: 166 pages
- Edition: 1
- Language: English
- Publisher: CRC Press
- Publication Date: 2021-09-27
- ISBN-10: 0367685566
- ISBN-13: 9780367685560
- Sales Rank: #0 (See Top 100 Books)
Many governments around the world are calling for the use of biometric systems to provide crucial societal functions, consequently making it an urgent area for action. The current performance of some biometric systems in terms of their error rates, robustness, and system security may prove to be inadequate for large-scale applications to process millions of users at a high rate of throughput.
This book focuses on fusion in biometric systems. It discusses the present level, the limitations, and proposed methods to improve performance. It describes the fundamental concepts, current research, and security-related issues. The book will present a computational perspective, identify challenges, and cover new problem-solving strategies, offering solved problems and case studies to help with reader comprehension and deep understanding.
This book is written for researchers, practitioners, both undergraduate and post-graduate students, and those working in various engineering fields such as Systems Engineering, Computer Science, Information Technology, Electronics, and Communications.
Cover Half Title Series Page Title Page Copyright Page Table of Contents Preface Editors’ Biographies Contributors Chapter 1 Deep Learning-Based Computer Vision: Security, Application and Opportunities 1.1 Introduction 1.1.1 Tasks in CV 1.1.2 Applications of CV 1.1.3 Object Detection 1.1.3.1 Model Output 1.1.4 Image Classification 1.1.5 Image Segmentation 1.1.6 Deep Learning 1.1.7 Samples of Deep Learning at Work 1.1.8 Convolution Neural Networks 1.2 Research Challenges of CV 1.3 Object Detection Methods 1.3.1 YOLO (You Only Look Once) 1.3.2 Mask R-CNN 1.3.3 SDD (Single Shot Multi-Box Detector) 1.3.4 Retina Net 1.3.5 Faster R-CNN 1.3.6 Cascade R-CNN 1.4 Image Classification Models 1.4.1 AlexNet 1.4.2 VGGNet 1.4.3 ResNet 1.4.4 SqueezNet 1.4.5 GoogleNet 1.5 Research Gaps 1.6 Conclusion and Future Work References Chapter 2 Recognition of Foggy Image for Surveillance Application 2.1 Introduction 2.2 Literature Review 2.3 Proposed Method 2.4 Result Analysis 2.4.1 Qualitative Analysis 2.4.2 Quantitative Analysis 2.5 Conclusion References Chapter 3 FishNet: Automated Fish Species Recognition Network for Underwater Images 3.1 Introduction 3.2 Literature Survey 3.3 Proposed Approach 3.3.1 Architecture of AlexNet 3.3.2 Fine Tuning the AlexNet Neural Network 3.3.3 Architecture of ResNet50 3.3.4 ResNet50 as Feature Extractor (Fish_Net_SVM) 3.4 Results 3.4.1 Data Set 3.4.2 Result Evaluation and Comparisons 3.5 Conclusion References Chapter 4 Person Identification in UAV Shot Videos by Using Machine Learning 4.1 Introduction 4.2 Related Work 4.2.1 Data Set 4.3 Proposed Work 4.4 Empirical Evaluation 4.4.1 Data Pre-Processing and Balancing of Data 4.4.2 Splitting of the Data Set 4.4.3 Choosing the Model 4.4.4 Face Detection Techniques 4.4.5 Viola Jones 4.4.6 Local Binary Pattern 4.4.7 Commercial-Off-the-Shelf System 4.4.8 Face Detection 4.4.9 Face Recognition 4.5 Conclusion and Future Work References Chapter 5 ECG-Based Biometric Authentication Systems Using Artificial Intelligence Methods 5.1 Introduction 5.2 Biometric Identification 5.2.1 Biometric Identification System Architecture 5.3 ECG-Based Biometric Identification 5.3.1 ECG Physiology 5.3.2 ECG Waveform 5.4 ECG signal Processing for Biometric Systems 5.4.1 Denoising 5.4.2 Segmentation 5.4.3 Feature Extraction 5.4.4 Feature Selection 5.5 ECG-Based Biometric Authentication Systems 5.6 Artificial Intelligence Methods for ECG-Based Biometric Authentication Systems 5.7 Conclusion References Chapter 6 False Media Detection by Using Deep Learning 6.1 Introduction 6.2 Related Work 6.3 Proposed Detection Algorithm for Detection of Fake Media 6.3.1 Background of Proposed Work 6.3.1.1 Face-Re Enactment 6.3.1.2 Deep-Fake 6.3.1.3 Generative Adversarial Network 6.3.2 Experimental Evaluation of Proposed Work 6.3.2.1 Output 6.4 Conclusion and Future Work References Chapter 7 Evaluation of Text-Summarization Technique 7.1 Introduction 7.2 Related Work 7.2.1 Term Frequency (Word Frequency) 7.2.2 Term Frequency-Inverse Document Frequency 7.2.3 Text Rank 7.2.4 Summa 7.2.5 Sentence Embeddings 7.3 Empirical Evidence 7.3.1 Corpus 7.3.2 Pre-Processing 7.4 Evaluation Method 7.5 Evaluation 7.5.1 Evaluation 7.5.1.1 TF-IDF 7.5.2 Metrics Implementation 7.5.3 Results 7.5.4 Discussion 7.6 Conclusion and Future Research References Chapter 8 Smart Metro Ticket Management by Using Biometric 8.1 Introduction 8.1.1 Metro Ticketing System 8.2 Related Work 8.2.1 Object Detection 8.2.2 Sign Language Recognition 8.2.3 Smart Parking System 8.3 Proposed Model for Metro Ticketing System 8.3.1 Architecture 8.3.1.1 React JS Application 8.3.1.2 Image Matching Model 8.3.1.3 API Gateway 8.3.1.4 Flask Server 8.4 Results and Analysis 8.4.1 Technology Stack 8.4.2 Use Case 8.5 Conclusion and Future Scope References Chapter 9 Internet of Things: Security Issues, Challenges and Its Applications 9.1 Introduction 9.2 Architecture of IoT 9.2.1 Perception Layer 9.2.2 Network Layer 9.2.3 Application Layer 9.3 Security Issues and Features of IoT 9.3.1 Security Features of IoT 9.3.2 IoT Security Risks 9.3.2.1 Lack of Observance on the Part of IoT Manufacturers 9.3.2.2 Lack of User Knowledge and Awareness 9.3.2.3 Issue of IoT Security in Device Update Management 9.3.2.4 Lack of Physical Hardening 9.3.2.5 Botnet Attacks 9.3.2.6 Industrial Espionage and Eavesdropping 9.3.2.7 Hijacking Your IoT Devices 9.3.2.8 Data Reliability Risks in Healthcare for IoT Security 9.3.2.9 Rogue IoT Devices 9.3.2.10 Crypto Mining with IoT Bots 9.4 IoT Challenges 9.5 Different Types of Attacks and Possible Solutions 9.6 IoT Applications 9.6.1 IoT in Industries 9.6.2 IoT in Personal Medical Devices 9.6.3 Smart Home Using IoT 9.6.4 IoT in Biometrics 9.7 Conclusion References Chapter 10 Wireless Sensor Network for IoT-Based ECG Monitoring System Using NRF and LabVIEW 10.1 Introduction 10.2 Proposed System 10.3 Hardware and Software Description 10.4 Circuit Description 10.5 Working of Proposed System 10.6 Results 10.7 Conclusion 10.8 Future Scope References Chapter 11 Towards Secure Deployment on the Internet of Robotic Things: Architecture, Applications, and Challenges 11.1 Introduction 11.1.1 Motivation and Contribution 11.2 Literature Survey 11.3 Internet of Robotic Things 11.4 Emerging IoRT Technologies 11.4.1 Sensors and Actuators 11.4.2 Communication Technologies 11.4.3 Connected Robotic Things 11.4.4 Virtual and Augmented Reality 11.4.5 Voice Recognition and Voice Control 11.5 Architecture of IoRT 11.5.1 Hardware Layer 11.5.2 Network Layer 11.5.3 Internet Layer 11.5.4 Infrastructure Layer 11.5.5 Application Layer 11.6 Applications of IoRT 11.6.1 Smart Home 11.6.2 Smart Office 11.6.3 Smart Workshop/Factory 11.6.4 Smart Nursing House 11.7 Research Challenges 11.7.1 Security 11.7.2 Authentication Issues 11.7.3 Computational Problem 11.7.4 Optimization 11.8 Conclusion References Index
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