Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
Preface
Acknowledgment
Editors
Contributors
1 The Evolution of Robotic Systems: Overview and its Application in Modern Times
1.1 Introduction
1.2 Robotic Systems
1.3 Computational Vision in Robotics
1.4 Technologies for Robotics
1.5 Robotic Systems in Healthcare
1.6 Scientific Review
1.7 Applications of Robotics
1.8 Future Trends
1.9 Conclusions
References
2 Development of a Humanoid Robot's Head with Facial Detection and Recognition Features Using Artificial Intelligence
2.1 Introduction
2.2 Construction of the Frame
2.3 Development of the Electronic Modules
2.3.1 PIR Sensor Module
2.3.2 Vision Sensor Module
2.3.3 Servo Motor
2.3.4 Raspberry Pi Microcontroller
2.4 Programming the Android's Head
2.4.1 Motion Tracking
2.4.2 Facial Detection and Recognition
2.5 Challenges
2.6 Conclusions
Appendix
Acknowledgment
References
References for Advance/Further Reading
3 Detecting DeepFakes for Future Robotic Systems
3.1 Introduction
3.2 Image Synthesis and DeepFake Technologies
3.2.1 Generative Adversarial Networks
3.2.2 GAN Image Models
3.2.2.1 General Image Synthesis
3.2.2.2 Face-Specific Synthesis
3.2.3 Other Face Swap Techniques
3.3 Deepfake Uses and Threats
3.3.1 Present Threats
3.3.2 Future Robotics and Deepfakes
3.4 Deepfake Databases for Research
3.4.1 Research Datasets
3.4.2 Deepfake Detection Challenge
3.5 Deepfake Detection Methods
3.5.1 General Methods
3.5.2 Specific Features
3.6 Image Segmentation
3.7 Multi-Task Learning for DeepFakes
3.8 Conclusions and Future Research
3.8.1 Summary
3.8.2 Concluding Remarks
3.8.3 Future Research Directions
References
4 Nanoscale Semiconductor Devices for Reliable Robotic Systems
4.1 Introduction
4.2 Bulk Metal Oxide Field Effect Transistor (MOSFET) Scaling Trend
4.2.1 Challenges of Bulk Complementary Metal Oxide Semiconductor (CMOS)
4.2.2 Limitations of Bulk MOSFET
4.2.3 Design Problems of Nanoscale CMOS
4.3 Nanoscale MOSFET Structures
4.3.1 Ultra-Thin Body (UTB) Mosfet
4.3.2 Double-Gate (DG) Moset
4.3.2.1 Advantages of Double-Gate Mosfet
4.3.3 Silicon On Insulator (SOI) Mosfet
4.3.4 Multiple-Gate MOSFET
4.4 FinFET Device Structures
4.4.1 FinFET's Pros and Cons
4.4.2 FinFET Device Modeling
4.5 Bulk MOSFET vs FinFET Leakage Currents
4.5.1 Subthreshold Leakage Currents
4.5.2 Gate Leakage Current
4.5.3 Robotic Application
4.6 Summary
References
5 Internet of Things for Smart Gardening and Securing Home from Fire Accidents
5.1 Introduction
5.2 Introduction of Different Sensors Used
5.2.1 Temperature Sensor
5.2.2 Flame Sensor
5.2.3 Soil Moisture Sensor
5.2.4 Global System for Mobile Communication
5.2.5 Arduino Uno Micro-Controller
5.3 Software Used
5.3.1 RFDMRP: River Formation Dynamics-Based Multi-Hop Routing Protocol
5.4 Existing Methods
5.5 Proposed Methods
5.5.1 Proposed System Architecture
5.5.2 Proposed Algorithm
5.5.3 Experimental Setup and Results
5.5.4 Applications
5.5.5 Advantages
5.6 Research Directions
References
References for Advance/Further Reading
6 Deep CNN-Based Early Detection and Grading of Diabetic Retinopathy Using Retinal Fundus Images
6.1 Introduction
6.2 Related Works
6.3 Proposed Method
6.3.1 Data Preprocessing
6.3.2 Data Augmentation
6.3.3 Network Architecture
6.3.4 Training
6.4 Experimental Results
6.4.1 Dataset
6.4.2 Performance Evaluation On Early-Stage Detection
6.4.3 Performance Evaluation On Severity Grading
6.4.4 Comparison Among Other Methods On Severity Grading
6.5 Conclusions
References
7 Vehicle Detection Using Faster R-CNN
7.1 Introduction
7.2 Related Work
7.3 Vehicle Detection Using Faster R-CNN
7.3.1 Faster R-CNN Outline
7.4 Experiments and Result Analysis
7.4.1 Training Dataset
7.4.2 Interpretation of Results
7.5 Conclusions
References
8 Two Phase Authentication and VPN-Based Secured Communication for IoT Home Networks
8.1 Introduction
8.1.1 Background
8.1.2 Authentication Protocols
8.2 Related Works
8.2.1 Wi-Fi Network-Based Security
8.2.2 PAuthkey Protocol
8.2.3 Two-Way Authentication Security Scheme On Existing DTLS Protocol
8.3 Network Model and Assumption
8.4 Proposed Solution
8.4.1 MAC Address-Based User Registration
8.4.2 Authentication Protocol
8.4.3 Data Transfer Security Using VPN
8.5 Conclusions and Future Work
8.5.1 Scope of Future Work
8.6 Conclusions
References
9 An Efficient Packet Reachability-Based Trust Management Scheme in Wireless Sensor Networks
9.1 Introduction
9.2 Background
9.2.1 Trust
9.2.2 Security Attacks
9.2.3 Motivation
9.3 Related Work
9.4 Proposed Trust Model
9.4.1 Recommendation (Feedback)-Based Trust
9.4.2 Evaluation of Total Trust
9.5 Performance Evaluation
9.6 Conclusions and Future Work
Acknowledgments
References
10 Spatial Domain Steganographic Method Detection Using Kernel Extreme Learning Machine
10.1 Introduction
10.2 Related Work
10.3 Background Concepts
10.3.1 Extreme Learning Machine
10.3.2 Kernel ELM
10.3.3 SPAM (Subtractive Pixel Adjacency Matrix) Feature Set
10.4 Proposed Methodology
10.5 Experimental Setup and Results
10.6 Conclusions
References
11 An Efficient Key Management Solution to Node Capture Attack for WSN
11.1 Introduction
11.2 Related Work
11.3 System Model and Problem Definition
11.3.1 Link Key
11.3.2 Threat Model
11.3.3 Network Model
11.3.4 Hash Function
11.3.5 Key Splitting Method
11.4 Proposed Scheme
11.4.1 Key Pool Generation
11.4.2 Random Key Assignment
11.4.3 Shared Key Discovery
11.4.4 Key Deletion
11.5 Security Analysis of the Proposed Scheme
11.6 Conclusion
References
12 Privacy Preservation and Authentication Protocol for BBU-Pool in C-RAN Architecture
12.1 Introduction
12.2 Related Work
12.3 Architecture of C-RAN
12.4 Advantages of Virtualization at C-BBU
12.5 Security Challenges in Virtualized C-BBU
12.6 Proposed Work
12.6.1 VM Request Phase
12.6.2 VM Registration and Authentication Phase
12.6.3 Host Utilization Calculation Phase
12.7 Proposed Security Protocol Verification and Authentication Procedure
12.7.1 Step 1: UE Authentication and Verification Step
12.7.2 Step 2: VM Authentication and Verification Step
12.8 Result and Simulation
12.9 Conclusion
References
13 Threshold-Based Technique to Detect a Black Hole in WSNs
13.1 Introduction
13.2 Related Work
13.3 Proposed Mechanism to Detect Black Hole Nodes in WSNs
13.3.1 Proposed Algorithm
13.3.2 Description of Proposed Mechanism
13.3.3 Data Flow Diagram (DFD) for the Proposed Solution
13.4 Results and Analysis
13.4.1 Simulation Results and Analysis
13.5 Conclusion
References
14 Credit Card Fraud Detection by Implementing Machine Learning Techniques
14.1 Introduction
14.2 Credit Card Fraud Issue
14.2.1 Current Methods of Fraud Detection
14.3 Application of Machine Learning Models for Fraud Detection
14.3.1 NaΓ―ve Bayes Classifier
14.3.2 Extreme Learning Machine
14.3.3 K-Nearest Neighbor
14.3.4 Multilayer Perceptron
14.3.5 Support Vector Machine
14.4 Dataset Used for the Model
14.5 Result and Discussion
14.5.1 Experimental Setup
14.5.2 Evaluation of Performance Parameters
14.5.2.1 Accuracy
14.5.2.2 Precision
14.5.2.3 Sensitivity
14.5.2.4 Specificity
14.5.2.5 F1 Score
14.5.3 Proposed Model
14.6 Conclusion
References
15 Authentication in RFID Scheme Based On Elliptic Curve Cryptography
15.1 Introduction
15.2 Elliptic Curve Cryptography Review
15.2.1 Elliptic Curve Discrete Logarithm Problem
15.2.2 Elliptic Curve Factorization Problem
15.2.3 DiffieβHellman Problem in Elliptic Curve
15.3 Review of Chou's Protocol
15.3.1 Chou's Protocol Setup Phase
15.3.2 Chou's Protocol Authentication Phase
15.4 Problems in Chou's Authentication Protocol
15.4.1 Problem in Tag Privacy
15.4.2 Problem in Mutual Authentication
15.4.3 Forward Traceability Problem
15.5 Proposed Protocol
15.5.1 Setup Phase
15.5.2 New Authentication Phase
15.6 Security Analysis of Proposed Protocol
15.6.1 Secure Against Tag Privacy Attack
15.6.2 Secure Against Mutual Authentication Problem
15.6.3 Secure Against Forward Traceability Problem
15.6.4 Secure Against Replay Attack
15.6.5 Secure Against Tag Impersonation Attack
15.6.6 Secure Against Modification Attack
15.7 Performance Analysis of Proposed Protocol
15.7.1 Analysis of Security Requirements of ECC-Basedprotocol
15.7.2 Analysis of Computational Cost
15.8 Conclusion
References
16 Iris-Based Privacy-Preserving Biometric Authentication Using NTRU Homomorphic Encryption
16.1 Introduction
16.2 Related Work
16.3 Feature Extraction From Iris Image
16.3.1 Iris Segmentation
16.3.2 Iris Normalization
16.3.3 Feature Extraction and Encoding
16.4 Proposed Method
16.4.1 NTRU Encryption
16.4.1.1 Advantages
16.4.1.2 Parameter Selection
16.4.2 Proposed Secure Domain Biometric Authentication
16.5 Experimental Results
16.6 Conclusion
References
Index