Safety, Security, and Reliability of Robotic Systems: Algorithms, Applications, and Technologies

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 Naïve 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 Diffie–Hellman 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