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