Intelligent Data Analytics IoT and Blockchain

Cover
Half Title
Title Page
Copyright Page
Table of Contents
About the Editors
Contributors
Chapter 1: Skin Cancer Classification Using Image Processing with Machine Learning Techniques
	1.1 Introduction
	1.2 Related Works
	1.3 Materials and Methods
		1.3.1 Dataset
		1.3.2 Preprocessing Operations
		1.3.3 LCNet Architecture
	1.4 Results and Discussion
	1.5 Conclusion
	References
Chapter 2: Trusted Location Information Verification Using Blockchain in Internet of Vehicles
	2.1 Introduction
	2.2 Related Work
	2.3 Trusted Location Information Verification Using Blockchain
		2.3.1 Assumptions
		2.3.2 System Model
		2.3.3 Location Sharing
		2.3.4 Location Verification
	2.4 Results and Simulation
		2.4.1 Location Leakage
		2.4.2 Channel Capacity Utilization
		2.4.3 Message Delivery Success Rate
		2.4.4 Processing Time
		2.4.5 Security Attack Resilience
	2.5 Conclusion
	References
Chapter 3: Comparative Analysis of Word-Embedding Techniques Using LSTM Model
	3.1 Introduction
	3.2 Related Works
	3.3 Methodology
		3.3.1 Dataset
		3.3.2 Word-Embedding Techniques
			3.3.2.1 Word2vec
			3.3.2.2 GloVe
			3.3.2.3 FastText
			3.3.2.4 BERT
		3.3.3 LSTM Deep Learning Classifier
		3.3.4 Evaluation Metric
	3.4 Results and Discussion
	3.5 Conclusion and Future Work
	References
Chapter 4: A Deep Learning Approach for Mask-Based Face Detection
	4.1 Introduction
	4.2 Related Work
	4.3 Dataset
	4.4 Proposed System
		4.4.1 TensorFlow
		4.4.2 Keras
		4.4.3 OpenCV
		4.4.4 Numpy
		4.4.5 Convolution Neural Network (CNN)
	4.5 System Flow Chart
	4.6 Evaluating Performance Using Performance Matrix
		4.6.1 Experiments and Result
	4.7 Conclusion and Future Scope
	References
Chapter 5: A Scalable System Architecture for Smart Cities Based on Cognitive IoT
	5.1 Introduction
	5.2 Related Work
		5.2.1 IoT Architectural Design
	5.3 Cognitive Computing-based IoT Architecture
		5.3.1 Cognitive Computing-based Smart City Architecture
	5.4 Assistive Technologies in Cognitive Computing
	5.5 Conclusion
	References
Chapter 6: Bagging-Based Ensemble Learning for Imbalanced Data Classification Problem
	6.1 Introduction
	6.2 Related Work
	6.3 Proposed Methodology
		6.3.1 Pre-processing
		6.3.2 Existing Classification Methods
			6.3.2.1 Radial Basis Function Neural Network
			6.3.2.2 Support Vector Machine
		6.3.3 Homogeneous Ensemble Classifiers
			6.3.3.1 Dagging
			6.3.3.2 ECOC
			6.3.3.3 Proposed Bagged RBF and SVM Classifiers
	6.4 Performance Evaluation Measures
		6.4.1 Cross-Validation Technique
		6.4.2 Criteria for Evaluation
	6.5 Experimental Results and Discussion
		6.5.1 Vehicle Dataset Description
		6.5.2 Experiments and Analysis
	6.6 Conclusion
	Acknowledgment
	References
Chapter 7: Design and Implementation of a Network Security Model within a Local Area Network
	7.1 Introduction
		7.1.1 Problem Statement
	7.2 Literature Review
	7.3 Design Methodology
		7.3.1 Design Consideration
		7.3.2 Architecture of a Network Security Model within a LAN
		7.3.3 Software Specification
	7.4 Implementation
		7.4.1 Network Security Model Implementation Requirements
		7.4.2 The Implemented Local Area Network (LAN) Model and its Configurations
		7.4.3 Results
			7.4.3.1 Ping Test
			7.4.3.2 Port Security
	7.5 Conclusion
	References
Chapter 8: Review of Modern Symmetric and Asymmetric Cryptographic Techniques
	8.1 Introduction
		8.1.1 Security Services
		8.1.2 Cryptography in Data Security
		8.1.3 Types of Cryptography
	8.2 Review of Literature
	8.3 Discussion
	8.4 Conclusion
	References
Chapter 9: Quantum Computing-Based Image Representation with IBM QISKIT Libraries
	9.1 Introduction
	9.2 Objective
		9.2.1 Main Objective
		9.2.2 Algorithm Steps
	9.3 Review of Work Implemented
		9.3.1 Quantum Circuit of 2 n Qubits for a 2 × 2 Image
		9.3.2 Tabular Representation of Intensity Values
		9.3.3 Grayscale Image Representation on a Quantum Circuit
	9.4 Advantages
	9.5 Result Analysis
	9.6 Conclusions
	References
Chapter 10: Source Authentication of Videos Shared on Social Media
	10.1 Introduction
	10.2 Literature Review
	10.3 Proposed Methodology
		10.3.1 Watermark Insertion
		10.3.2 Watermark Extraction
	10.4 Experimental Evaluation
	10.5 Discussion
	10.6 Limitation
	10.7 Conclusion
	References
Chapter 11: Task Scheduling Using MOIPSO Algorithm in Cloud Computing
	11.1 Introduction
	11.2 Related Work
	11.3 Problem Formulation
	11.4 System Model
	11.5 Traditional Approach
	11.6 Proposed Multi-objective Improved Particle Swarm Optimization
	11.7 Experiment
		11.7.1 Experimental Set-Up
		11.7.2 Experimental Parameters
		11.7.3 Experiment, Result and Discussion
	11.8 Conclusion and Future Work
	References
Chapter 12: Feature Selection-Based Comparative Analysis for Cardiovascular Disease Prediction Using a Machine Learning Model
	12.1 Introduction
	12.2 Related Work
	12.3 Proposed Methodology
		12.3.1 Dataset
	12.4 Result Analysis
	12.5 Conclusion
	References
Chapter 13: Use of Cryptography in Networking to Preserve Secure Systems
	13.1 Introduction
		13.1.1 Characteristics of Cryptography
		13.1.2 Types of Cryptography
		13.1.3 Cryptanalysis
	13.2 Cryptographic Primitives
	13.3 Applications of Cryptography
	13.4 Issues in Network Security
	13.5 Issues in Cryptography
	13.6 Conclusion and Future Directions
	References
Chapter 14: Issues and Challenges of Blockchain in Healthcare
	14.1 Introduction
		14.1.1 Reasons for Adopting Block Chain
	14.2 Design
		14.2.1 Terms and Definitions
		14.2.2 Interplanetary File System
	14.3 Related Work
	14.4 Applications and Challenges of Block Chain in Healthcare
		14.4.1 Applications
		14.4.2 Challenges
		14.4.3 Strategies and India-centric Outcomes Targeted towards Block Chain
	14.5 Differences between Current and Proposed Systems
		14.5.1 Current System
		14.5.2 Proposed System
		14.5.3 Benefits
		14.5.4 Implementation
	14.6 System Architecture
	14.7 Conclusion
	References
Chapter 15: Accident Prediction by Vehicle Tracking
	15.1 Introduction
	15.2 Related Work
	15.3 Methodology
		15.3.1 Object Detection and Classification
		15.3.2 Object Tracking
		15.3.3 Speed Estimation
		15.3.4 Accident Prediction
	15.4 Results Analysis
	15.5 Performance Analysis
	15.6 Conclusion and Future Work
	References
Chapter 16: Blockchain-Based Cryptographic Model in the Cloud Environment
	16.1 Introduction
	16.2 Related Works
	16.3 Proposed Methodology
		16.3.1 Protection of Authentication
		16.3.2 Ownership Protection
		16.3.3 Identity Mapping Validation
	16.4 Future Work
	16.5 Conclusions
	References
Chapter 17: Big-Data Analytics in Disaster Management
	17.1 Introduction
	17.2 A Disaster-resilience Strategy Based on Big Data
	17.3 Disaster Management
	17.4 Characteristics of Big Data
	17.5 Application of Big Data in Disaster Management
	17.6 Comparative Analysis of the Methods Employed
	17.7 Conclusion
	References
Chapter 18: Fuzzy Minimum Spanning Tree Calculation-Based Approach on Acceptability Index Method
	18.1 Introduction
		18.1.1 Literature Review
		18.1.2 Motivation and Contribution
	18.2 Preliminaries
		18.2.1 Triangular Fuzzy Number
		18.2.2 Trapezoidal Fuzzy Number
		18.2.3 Yager Index
		18.2.4 The π 2 Membership Function
		18.2.5 The Minimum Operation of Two π 2 - Type Fuzzy Numbers
		18.2.6 The Acceptability Index
		18.2.7 The α - Cut Interval for Fuzzy Number
		18.2.8 On α - Cut Interval for Fuzzy Interval
		18.2.9 On the Convex Index
	18.3 Algorithm for Fuzzy Minimum Spanning Tree
		18.3.1 Fuzzy Minimum Spanning Tree Based on the Acceptability Index
		18.3.2 Fuzzy Minimum Spanning Tree Algorithm Using Convex Index
		18.3.3 Verification Using Yager’s Index
		18.3.4 Comparison
	18.4 Conclusion and Future Scope
	References
Chapter 19: Encoder/Decoder Transformer-Based Framework to Detect Hate Speech from Tweets
	19.1 Introduction
	19.2 Related Work
	19.3 Preliminaries
		19.3.1 BERT (Bidirectional Encoder Representations from Transformer)
		19.3.2 GPT-2 (Generative Pretrained Transformer)
	19.4 Framework of the System
	19.5 Conclusion
	References
Chapter 20: Understanding Dark Web Protection against Cyber Attacks
	20.1 Introduction
	20.2 Elements of the Dark Web
		20.2.1 Guard and Middle Relays
		20.2.2 The Relay is Used to Exit the TOR Circuit
		20.2.3 Bridge
	20.3 Criminal Activity
		20.3.1 Trafficking
		20.3.2 Information Leakage
		20.3.3 Proxying
		20.3.4 Fraud
		20.3.5 Onion Cloning
	20.4 Defense Mechanisms and Cyber Attacks
		20.4.1 Correlation Attacks
		20.4.2 Congestion Attacks
		20.4.3 Distributed Denial of Service (DDoS) Attacks
		20.4.4 Phishing
		20.4.5 Malware
	20.5 Conclusion
	References
Chapter 21: Various Elements of Analysis of Authentication Schemes for IoT devices: A Brief Overview
	21.1 Introduction
	21.2 Motivation
	21.3 Informal Analysis
		21.3.1 Adversary Model
		21.3.2 Taxonomy of Attacks
	21.4 Formal Analysis
	21.5 Performance Analysis
	21.6 Simulator/Computation Analysis tools
	21.7 Conclusion and Future Work
	Declarations
	Conflict of Interest
	References
Chapter 22: A Study of Carbon Emissions in the Transport Sector
	22.1 Introduction
	22.2 Literature Review
	22.3 Data Collection, Analysis and Visualization
	22.4 Technologies for Balancing Emissions
		22.4.1 Artificial Intelligence (AI)
		22.4.2 Machine Learning (ML)
		22.4.3 Internet of Things (IoT)
		22.4.4 Renewable Energy
		22.4.5 Electric Vehicles (EVs)
		22.4.6 Direct Air Capture (DAC)
		22.4.7 Bioenergy with Carbon Capture and Storage (BECCS)
	22.5 Conclusion and Future Scope
	References
Chapter 23: An Exploration of Blockchain Technology: Applicability, Limitations, and Opportunities
	23.1 Introduction
	23.2 Classification of Blockchain
		23.2.1 Permission-Less Blockchain
		23.2.2 Permissioned Blockchain
	23.3 Consensus Mechanism
		23.3.1 Proof of Work (PoW)
		23.3.2 Proof of Stake (PoS)
		23.3.3 Practical Byzantine Fault Tolerance (PBFT)
	23.4 Use Cases of Blockchain Technology
		23.4.1 Blockchain in the Supply Chain
		23.4.2 Blockchain for Financial Applications
		23.4.3 Blockchain for Non-financial Applications
	23.5 Conclusion and Future Research Areas
	References
Chapter 24: A Survey of Security Challenges and Existing Prevention Methods in FANET
	24.1 Introduction
	24.2 FANET and Communication Protocols
		24.2.1 Based on Physical Layer
		24.2.2 Based on MAC Layer
		24.2.3 Based on Network Layer/Routing Protocols
	24.3 Security Attacks and Issues
		24.3.1 Active Attacks
		24.3.2 Passive Attacks
		24.3.3 Other Types of Attack
	24.4 Literature Review and Related Works
	24.5 Security Solutions in Tabular Format
	24.6 Conclusion
	References
Chapter 25: MENA Sukuk Price Prediction Modeling using Prophet Algorithm
	25.1 Introduction
	25.2 Literature Review
	25.3 Research Methodology
		25.3.1 Prophet Model
	25.4 Data Representation
	25.5 Experimental Results and Analyses
		25.5.1 Evaluation Metrics
		25.5.2 Result and Analyses
	25.6 Conclusion and Implications
	Note
	References
Chapter 26: Cancer Biomarkers Identification from Transcriptomic Data Using Supervised Machine Learning Approaches
	26.1 Introduction
	26.2 Microarrays in Cancer
	26.3 Supervised Machine Learning in Cancer Biomarkers Detection
	26.4 Conclusion
	Acknowledgment
	References
Chapter 27: Development of a Secured and Interoperable Multi-Tenant Software-as-a-Service Electronic Health Record System
	27.1 Introduction
		27.1.1 Problem Statement
	27.2 Literature Review
	27.3 Design Methodology
		27.3.1 Architecture of a Secured and Interoperable Multi-tenant SaaS Electronic Health Record System
		27.3.2 Components of the Architectural Design
		27.3.3 Flowchart
	27.4 Implementation
		27.4.1 The Security Framework
	27.5 Conclusion
	References
Chapter 28: Investigating Classification with Quantum Computing
	28.1 Introduction
	28.2 Quantum Computation Background
		28.2.1 Circuits and Measurements
	28.3 Quantum Machine Learning
		28.3.1 Quantum Encoding
	28.4 Literature Review
	28.5 Quantum Machine Learning Algorithms
	28.6 Challenges and Future Scope
	28.7 Conclusion
	References
Chapter 29: A Comprehensive Analysis of Techniques Offering Dynamic Group Management in a Cloud Computing Environment
	29.1 Introduction
	29.2 Existing Solutions Based on Encryption Mechanisms
	29.3 Kerberos-Based Solutions
	29.4 Access Control-Based Solutions
	29.5 Conclusion
	References
Chapter 30: Improved YOLOv5 with Attention Mechanism for Real-Time Weed Detection in the Paddy Field: A Deep Learning Approach
	30.1 Introduction
	30.2 Related Works
	30.3 Proposed System
		30.3.1 Improved YOLOv5 Algorithm
		30.3.2 Attention Mechanism
		30.3.3 CBAM
		30.3.4 ECA-Net
	30.4 Experiments
		30.4.1 Implementation Details
		30.4.2 Evaluation Metrics
		30.4.3 Training
		30.4.4 Ablation Studies
	30.5 Performance Analysis
		30.5.1 Comparison with State-of-the-Art Approaches
	30.6 Conclusion
	References
Index