Blockchain Technology in Healthcare Applications: Social, Economic, and Technological Implications

Cover
Half Title
Series Page
Title Page
Copyright Page
Table of Contents
Preface
Editors
Contributors
Chapter 1 Blockchain for Securing Internet of Things – A Layered Approach
1.1 Introduction
1.2 Blockchain Principles
1.2.1 Overview
1.2.2 Characteristics
1.2.3 Transaction Process
1.3 IoT Fundamentals
1.3.1 Objects Layer
1.3.2 Network Layer
1.3.3 Service Management Layer
1.3.4 Application Layer
1.3.5 Business Layer
1.3.6 IoT Components
1.4 Security Issues of IoT
1.4.1 Security Issues of Objects Layer
1.4.2 Security Issues of Network Layer
1.4.3 Security Issues of Middleware Layer
1.4.4 Security Issues of Application Layer
1.4.5 Security Issues of Business Layer
1.5 Blockchain-Based Solution
1.6 Challenges and Future Work
1.6.1 Heterogeneity of Devices
1.6.2 Hardware and Firmware Vulnerabilities
1.6.3 Scalability
1.6.4 Limitations in IoT-Friendly Consensus Mechanism
1.7 Conclusion
References
Chapter 2 A Novel Framework for Robust Data Collection in Industrial IoT Based on Proof-of-Stake Algorithm
2.1 Introduction: Industrial Internet of Things
2.2 IIoT – Use Cases
2.3 Blockchain and Proof-of-Stake Algorithm
2.4 Integrating Proof-of-Stake Model into IIoT
2.5 Proposed Algorithm
2.6 Simulation and Results
2.7 Conclusion
References
Chapter 3 Blockchain Technology for IoT Security of Smart City Applications
3.1 Introduction
3.2 Blockchain Overview
3.2.1 Introducing Blockchain
3.2.2 Block Structure
3.2.3 Consensus Protocols
3.2.4 Smart Contracts
3.3 Smart City and IoT Applications
3.3.1 General Overview
3.3.2 Complex Events
3.4 IoT and Blockchain Integration
3.4.1 IoT Security Deflation
3.4.2 IoT Applications Architecture
3.4.3 Blockchain as a Component in the IoT Architecture
3.4.3.1 Blockchain as a Secure Data Store
3.4.3.2 Blockchain as an Authentication Manager
3.5 Conclusion
References
Chapter 4 Cryptocurrency Revolution: Bitcoin Time Forecasting & Blockchain Anomaly Detection
4.1 Introduction
4.2 Background
4.2.1 ARIMA
4.2.2 RNN
4.2.3 Prophet
4.2.4 Clustering
4.2.5 XGBoost
4.3 Literature Review
4.4 Design and Implementation
4.4.1 ARIMA Model
4.4.2 XGBoost Model
4.4.3 Anomaly Detection
4.5 Performance Evaluation
4.6 Conclusion and Future Scope
References
Chapter 5 Applications of AI, IoT, and Robotics in Healthcare Service Based on Several Aspects
5.1 Introduction: Background
5.1.1 Outline
5.2 Literature Survey
5.3 Robotics in Healthcare
5.4 AI in Healthcare
5.5 Healthcare with IOT based on Fusion of AI and ML
5.5.1 Clinic Robots
5.5.2 Careful Robot
5.5.3 Care Robot
5.5.4 Exoskeletons
5.6 Internet of Healthcare
5.6.1 Security
5.6.2 Application of IoT in Healthcare
5.6.3 The Advantages of IoT in Healthcare
5.7 Conclusion and Future Scope
References
Chapter 6 A Machine Learning Approach to Improve the Pharmaceutical Industry Machinery: Case of Zimbabwe
6.1 Introduction
6.2 Background and Status Quo of the Zimbabwean Pharmaceutical Industry
6.2.1 The Manufacturing Process of Pharmaceuticals in Zimbabwe
6.3 Pharmaceutical Industry Equipment, Processes, and Standards
6.3.1 Manufacturing of Pharmaceuticals
6.3.2 Machine Learning
6.3.3 Role of AI in Pharmaceuticals Industry
6.3.3.1 AI in Drug Discovery
6.3.3.2 AI in Process Control and Quality Assurance
6.3.4 The Adoption of AI, with Emphasis on ML in the First World to Improve Pharmaceutical Manufacturing
6.3.4.1 Drug Development
6.3.4.2 Manufacturing Control and QA
6.3.4.3 GEA (Belgium), a Pharmaceutical Equipment Manufacturer Who has Applied AI and ML to Enable CPM
6.4 Methods and Materials
6.4.1 Data Collection
6.4.2 Programming
6.4.3 Observations and Interviews
6.4.4 Statistical Tools
6.4.5 Data Availability Statement
6.5 Results and Discussion
6.5.1 Interview with the Managing Director
6.5.2 Questionnaire to the Production Manager
6.5.3 Interviews with Operators
6.5.4 Manufacturing Process Overview of Ibuprofen 400 mg Tablets and Review of the Batch Manufacturing Record
6.5.4.1 Product Costing Review
6.5.4.2 A Machine Learning Algorithm for Tablet Weight Control on a Tablet Compression Machine
6.5.5 Impact of Machine Learning Algorithm Application on a Tabletting Machine
6.6 Conclusions and Recommendations
6.6.1 Conclusions
6.6.2 Recommendations
References
Chapter 7 Regression Analysis for Prediction of Blood Pressure from Health Parameter
7.1 Introduction
7.2 Literature Review
7.3 Proposed Method
7.3.1 Data Collection
7.3.2 Model
7.3.3 Android Application
7.4 Result and Discussions
7.4.1 Limitations and Future Scope
7.5 Conclusions
Acknowledgment
References
Chapter 8 Revolutionizing Healthcare: Decentralized Data Management of IoT Devices Using Blockchain Technology
8.1 Introduction
8.1.1 Healthcare
8.1.2 Advancements in Healthcare
8.1.3 Internet of Things
8.1.4 Big Data
8.2 Internet of Medical Things
8.2.1 Internet of Informative Medical Things
8.2.2 Internet of Intelligent Medical Things
8.3 Architecture of Decentralized IoMT Using BCT
8.4 Healthcare Data Management
8.4.1 Patient
8.4.2 Medical Professionals
8.4.3 Medical Insurance
8.4.4 Ambulance Services
8.4.5 Tracking of Medicines
8.4.6 Clinical Laboratory
8.5 Decentralized Management of IoT Devices
8.5.1 Preventive Healthcare
8.5.2 Care from Home
8.5.3 Intensive Care
8.5.4 Diagnostic Healthcare
8.5.5 Rehabilitation Healthcare
8.5.6 Chronicle Healthcare
8.5.7 Clinical Trials
8.6 Performance Evaluation
8.7 Recent Blockchain Technologies in Healthcare
8.7.1 Healthcare IoMT Devices
8.7.2 Cloud Computing
8.7.3 Fog Computing
8.7.4 Edge Computing
8.7.5 Artificial Intelligence
8.7.6 Data Encryption
8.8 Challenges in Decentralized Management of IoMT Devices in Healthcare
8.8.1 Challenges in IoMT
8.8.1.1 Device Vulnerability
8.8.1.2 Energy Challenges
8.8.1.3 Security Update Challenge
8.8.1.4 Heterogeneity of Devices
8.8.1.5 Challenge of Scalability
8.8.1.6 Limited In-built Memory
8.8.1.7 Challenges of Accuracy
8.8.1.8 Challenge of Standardization
8.8.2 Challenges in Decentralized Management of IoMT
8.8.2.1 Challenges in Cyber Security
8.8.2.2 Challenge of Scalability
8.8.2.3 Challenge of Investment
8.8.2.4 Regulatory Challenges
8.8.2.5 Challenge of Infrastructure
8.8.2.6 User Challenges
8.8.2.7 Challenge of Immutability
8.9 Conclusion
References
Chapter 9 Introduction to Blockchain and Smart Contract – Principles, Applications, and Security
9.1 Introduction
9.2 Blockchain
9.2.1 Block Structure
9.2.1.1 Block Header
9.2.1.2 Block Body
9.2.2 Process Flow in Block Mining
9.2.3 Features of Blockchain
9.2.3.1 Immutability
9.2.3.2 Decentralization
9.2.3.3 Transparency
9.2.3.4 Pseudonymity
9.2.3.5 Non-repudiation
9.2.3.6 Fast Processing
9.2.3.7 Low Cost
9.2.3.8 Provenance
9.2.3.9 Auditability
9.2.3.10 Availability
9.2.3.11 Automation
9.2.4 Types of Blockchain
9.2.4.1 Public Blockchain
9.2.4.2 Private Blockchain
9.2.4.3 Consortium Blockchain
9.3 Smart Contracts
9.3.1 Introduction
9.3.2 Features of Smart Contracts
9.3.2.1 Decentralized Operation
9.3.2.2 Immutability
9.3.2.3 Elimination of a Third Party
9.3.2.4 Autonomous Execution
9.3.2.5 Transparency
9.3.2.6 Accuracy
9.3.2.7 Speed
9.3.3 Different Blockchain Platforms Supporting Smart Contracts
9.3.3.1 Ethereum
9.3.3.2 Hyperledger Fabric
9.3.3.3 Corda
9.3.3.4 Stellar
9.3.3.5 EOS
9.4 Applications of Blockchain and Smart Contracts
9.5 Security Aspects of Blockchain and Smart Contracts
9.6 Conclusion
References
Chapter 10 Blockchain Technology in Healthcare: A Systematic Review
10.1 Introduction
10.2 The Blockchain Technology Basic Concepts
10.2.1 Blockchain Process and Categories
10.2.2 Smart Contracts and Ethereum Platform
10.3 The Blockchain for Healthcare
10.3.1 Patient Data Management
10.3.2 Security and Privacy in Blockchain-Healthcare
10.3.3 Drug/Pharmaceutical Supply Chain Management
10.3.4 Clinical Trial Certification
10.4 Conclusion
References
Chapter 11 Blockchain for IoT-Based Healthcare: Overview of Security and Privacy Issues
11.1 Introduction
11.2 The Security Attacks in IoT-Based Healthcare Applications
11.3 Security Requirements in IoT-Based Healthcare Applications
11.4 Security Solutions in IoT-Based Healthcare Applications
11.4.1 Fog Computing-Based Solutions
11.4.2 Software Defined Networking-Based Solutions
11.4.3 Blockchain-Based Solutions
11.4.4 Lightweight Cryptography-Based Solutions
11.4.5 Artificial Intelligence-Based Solutions
11.4.6 Homomorphic and Searchable Encryption-Based Solutions .
11.5 Conclusion
References
Chapter 12 Effective Management of Personal Health Records using Blockchain Technology
12.1 Introduction
12.1.1 Motivation
12.1.2 Major Contribution
12.1.3 Chapter Organization
12.2 Review of the Literature
12.2.1 Method
12.2.2 Results
12.2.2.1 General Observations
12.2.2.2 Specific Observations
12.3 Anticipated Trends in the Future of Blockchain Technology in PHRs
12.4 Key Success Factors for Effective Implementation of BT in PHR
12.5 Conclusions
References
Chapter 13 Interoperability, Anonymity and Privacy Issues in Blockchain for Healthcare Systems
13.1 Introduction
13.2 Healthcare and Its Evolution
13.3 Role of Blockchain Technology
13.3.1 Types of Blockchain Network
13.3.2 Validity Process in Blockchain
13.3.3 Blockchain for Healthcare Ecosystem
13.3.4 Blockchain in Pharmaceuticals: Challenges and Opportunities
13.3.4.1 Throughput
13.3.4.2 Latency
13.3.4.3 Security
13.3.4.4 Resource Consumption
13.3.4.5 Centralization
13.4 Critical Challenges and Blockchain-Based Solutions
13.4.1 Data Collection and Storage
13.4.2 Data Sharing and Interoperability
13.4.3 Securing Data and Managing
13.5 Healthcare Supply Chain
13.5.1 Blockchain for Supply Chain
13.5.2 Pharmaceutical Traceability using Blockchain
13.5.3 Pharma Supply Chain Tracker using Blockchain
13.6 Conclusion and Future Research Directions
References
Chapter 14 Blockchain in the Pharmaceutical Industry for Better Tracking of Drugs with Architectures and Open Challenges
14.1 Introduction
14.2 Overview of Blockchain
14.3 Overview of Drug Tracking in the Healthcare Domain
14.4 Architectures for Drug Tracking Based on Blockchain
14.4.1 Hyperledger Fabric Blockchain-Based Architecture
14.4.1.1 Drug Tracking Flow with Hyperledger Fabric Blockchain Architecture
14.4.2 Hyperledger Besu Blockchain-Based Architecture
14.4.2.1 Drug Tracking Flow with Hyperledger Besu Blockchain-Based Architecture
14.4.3 Ethereum-Based Architecture
14.4.3.1 Flow of Drug Tracking with Ethereum Based Architecture
14.4.4 Comparison of Hyperledger Fabric, Hyperledger Besu, and Ethereum Architectures
14.5 Discussion and Open Challenges
14.5.1 Stakeholder Agreement
14.5.2 Interoperability
14.5.3 Implementation Cost
14.5.4 Attack and Vulnerabilities
14.5.5 Lack of Standardized
14.6 Conclusion
References
Chapter 15 Securing Privacy and Integrity of Patient’s Data in Healthcare 4.0 by Countering Attack using Blockchain
15.1 Introduction
15.2 Healthcare 4.0
15.2.1 Evolution of Healthcare
15.2.2 Drivers for Healthcare 4.0
15.2.3 Healthcare 4.0 and Its Main Technology
15.2.4 Healthcare 4.0 Applications
15.3 Blockchain
15.3.1 Types of Blockchain
15.3.1.1 Private Blockchain
15.3.1.2 Public Blockchain
15.3.1.3 Consortium Blockchain
15.3.2 Architecture of Blockchain
15.3.2.1 Data Layer
15.3.2.2 Network Layer
15.3.2.3 Consensus Layer
15.3.2.4 Incentive Layer
15.3.2.5 Contract Layer
15.3.2.6 Application Layer
15.3.3 Consensus Protocols
15.3.3.1 Proof of Work
15.3.3.2 Proof of Stake
15.3.3.3 Delegated PoS
15.3.3.4 Proof of Burn
15.3.3.5 Proof of Elapsed Time
15.3.3.6 Proof of Capacity
15.3.3.7 Practical Byzantine Fault Tolerance
15.3.3.8 Proof of Authority
15.4 Cyber Security in Healthcare 4.0
15.4.1 Network Vulnerability and Attacks
15.4.2 Policy Check Based Vulnerability and Attack
15.4.3 Sensor, Physical Vulnerability and Attacks
15.5 Achieving Privacy and Security using Blockchain for Healthcare 4.0
15.6 Conclusion and Future Research Direction
References
Index