Blockchain for 5G Healthcare Applications: Security and privacy solutions

Contents
About the Editor
Preface
1 Security and privacy requirements in 5G healthcare
	1.1 Introduction
		1.1.1 How will 5G affect health-care system?
			1.1.1.1 Telemedicine
			1.1.1.2 Monitoring of patients living in remote areas
			1.1.1.3 Augmented and virtual reality
			1.1.1.4 Analysis of data
			1.1.1.5 Decentralization of the ideal health-care model
			1.1.1.6 Transfer of large files
		1.1.2 Integration of blockchain, 5G and healthcare
			1.1.2.1 Challenges for the blockchain system
				1.1.2.1.1 Scalability
				1.1.2.1.2 Smart contracts
				1.1.2.1.3 Standardization and regulations
				1.1.2.1.4 Transaction and cloud infrastructure costs
				1.1.2.1.5 Data privacy
			1.1.2.2 Naming, registration, and reputation
		1.1.3 Contributions of this chapter
		1.1.4 Motivation
	1.2 Related work
		1.2.1 Research gap
	1.3 Challenges associated with the present health-care system
		1.3.1 Challenges with health records
		1.3.2 Universal access limitations
		1.3.3 Long-term constant care burden
		1.3.4 Challenges for aging populations
		1.3.5 Limitation of the resources
		1.3.6 Problems associated with health-care information systems
		1.3.7 Lack of data driven
		1.3.8 Health-care disparities
		1.3.9 Standardization and interoperability
		1.3.10 Effective regulation
		1.3.11 Data privacy and research needs
	1.4 5G technology
		1.4.1 Millimeter waves
		1.4.2 Small cells
		1.4.3 Big multiple input/output system
		1.4.4 Beamforming
		1.4.5 Full duplex
		1.4.6 Software-defined networks
	1.5 Technical challenges and the path to 5G
		1.5.1 Trust management
		1.5.2 Encryption method
		1.5.3 Access control
		1.5.4 Privacy
	1.6 Security and privacy
		1.6.1 Authentication
		1.6.2 Confidentiality
		1.6.3 Availability
		1.6.4 Integrity
	1.7 5G and health-care opportunities
		1.7.1 Fast and intelligent networks
		1.7.2 Back-end services
		1.7.3 Low latency
		1.7.4 Applications of 5G in healthcare
			1.7.4.1 Smart clothing
			1.7.4.2 Diagnosis services in rural areas
			1.7.4.3 Management in hospitals
			1.7.4.4 Use of robots
			1.7.4.5 Monitoring of health-care data
			1.7.4.6 Imaging
			1.7.4.7 Diagnostics
			1.7.4.8 Data analytics and treatment
		1.7.5 Impact of 5G on medical access, quality, and cost
		1.7.6 The impact of 5G on healthcare
			1.7.6.1 Continuous monitoring
			1.7.6.2 Predictive analytics
			1.7.6.3 Impact on business models
			1.7.6.4 Remote diagnosis and imaging
			1.7.6.5 Improved state of art
	1.8 Conclusions
	References
2 Ethical and legal aspects of using blockchain technology for 5G-based health-care systems
	Abstract
	2.1 Introduction
		2.1.1 Research contribution
		2.1.2 Motivation
		2.1.3 Organization
	2.2 Blockchain technology and 5G in healthcare
		2.2.1 Edge computing
		2.2.2 Augmented and virtual reality
		2.2.3 Ambulance drones
		2.2.4 5G on mobile app development
	2.3 Issues of privacy and security
	2.4 Security spectrum of 5G-enabled devices
		2.4.1 Privacy
		2.4.2 Transparency
		2.4.3 No single point of failure
	2.5 Key issues and stakeholders
		2.5.1 Tweaking of IoT devices
			2.5.1.1 Stakeholder profile: Individuals and industries
		2.5.2 No protocol right now to govern them all
			2.5.2.1 Stakeholder profile: Individuals and government
		2.5.3 Blockchain owning
			2.5.3.1 Stakeholder profile: individuals
		2.5.4 Energy inefficiency
			2.5.4.1 Stakeholder profile: industries
		2.5.5 High-altitude limitations
			2.5.5.1 Stakeholder profile: industries
		2.5.6 Man-in-the-middle attack
			2.5.6.1 Stakeholder profile: individuals
	2.6 Trust and regulations
	2.7 Regulatory bodies and the role of the government
	2.8 Future challenges
		2.8.1 Cost
		2.8.2 Infrastructure
		2.8.3 Security and privacy
		2.8.4 Frequency bands
		2.8.5 Training and education challenges
	2.9 Conclusion
	References
3 Blockchain-based 5G-enabled health-care system: an analysis of security and privacy issues
	Abstract
	3.1 Introduction
		3.1.1 Blockchain
		3.1.2 Types of blockchain
		3.1.3 5G technology
		3.1.4 Healthcare
	3.2 Blockchain integration with 5G
		3.2.1 Blockchain for 5G advancements
	3.3 Need of blockchain in healthcare
	3.4 Blockchain-based health-care system
	3.5 Security and privacy properties requirements in healthcare
	3.6 Security and privacy techniques
	3.7 Healthcare-based application in blockchain
	3.8 Conclusion
	References
4 Enhanced blockchain technology associated with IoT for secure and privacy communications in 5G
	4.1 Introduction
	4.2 Design process of blockchain-based systems
	4.3 IoT–with 5G and blockchain
		4.3.1 Requirements of IoT
		4.3.2 Benefits of 5G
		4.3.3 Impact of blockchain technology on digital commerce
		4.3.4 Impact of blockchain on IoT
	4.4 5G technology for greater connectivity
		4.4.1 Mobile payment networks to worldwide communication
		4.4.2 How blockchain and 5G help secure versatile banking
		4.4.3 How will 5G WiFi enhance blockchain-based crypto assets?
		4.4.4 Scaling of blockchain functionality by 5G
		4.4.5 5G for boosting keen agreements credibility
		4.4.6 How 5G will increase network volume for blockchain improvement?
		4.4.7 Will 5G bargain blockchain innovation’s latent capacities?
	4.5 5G-based blockchain distributed ledger technology
	4.6 Secure mobile banking using 5G and blockchain
	4.7 5G benefits to blockchain and crypto users
		4.7.1 5G affect on revolutionizing blockchain
		4.7.2 How 5G authorizes smart contracts
	4.8 Blockchain in defense to secure communications
	4.9 Key issues in blockchain in communications
		a. Companywide collaboration
		b. Voice security as a communications channel
	4.10 5G challenges facing deployment
		a. Building mind-boggling and thick systems
		b. Maintaining running and security costs low
		c. Meeting low-inactivity necessities
		d. Managing new well-being inconveniences
		e. Recurrence groups
		f. Deployment and protection
		g. Cost to assemble price to adopt 5G in smart applications
		h. Laws and principles
		i. Modernizing rules to make 5G a reality
		j. Security and protection
	4.11 New opportunities for 5G applications
		A. Industrial and artificial consciousness
		B. Automotive 5G with self-ruling vehicles
		C. Part and resistance
	4.12 Blockchain works to secure communications
		4.12.1 Centralized, distributed, and decentralization networking
		4.12.2 Coding modern technologies
		4.12.3 Vulnerabilities in existing communications protocols
		4.12.4 Weaknesses in packetization
		4.12.5 Securing community packets with blockchain
		4.12.6 Weaknesses in net protocol addresses
		4.12.7 Protecting IP addresses with decentralized communications
	4.13 Propose framework along with blockchain technology
	4.14 Case study
	4.15 Chapter summary and conclusions
	References
5 5G-driven radio framework for proficient smart health-care institutions
	5.1 Introduction
	5.2 Motivation and contribution
	5.3 Waveform techniques for 5G
		5.3.1 OFDM
		5.3.2 FBMC
		5.3.3 NOMA
		5.3.4 UFMC
	5.4 Detection systems
		5.4.1 ZF
		5.4.2 MMSE scheme
		5.4.3 Beamforming
	5.5 Simulation results
	5.6 Case studies
	5.7 Conclusion
	References
6 Traditional vs. the blockchain-based architecture of 5G healthcare
	6.1 Introduction
		6.1.1 Motivations
		6.1.2 Structure of the chapter
	6.2 5G-based smart healthcare industry: challenges, benefits, and use cases
		6.2.1 5G healthcare challenges
		6.2.2 5G healthcare benefits
			6.2.2.1 Fast data transfer
			6.2.2.2 Personalized care
			6.2.2.3 Futuristic application enabling
		6.2.3 5G healthcare use cases
			6.2.3.1 Telemedicine
			6.2.3.2 Large data transfer
			6.2.3.3 Real-time remote monitoring
			6.2.3.4 Sensors
	6.3 Traditional 5G healthcare architecture
		6.3.1 5G healthcare overall architecture
		6.3.2 5G healthcare infrastructure architecture
		6.3.3 5G healthcare RAN architecture
		6.3.4 5G healthcare core network architecture
	6.4 Blockchain-based 5G healthcare architecture
		6.4.1 Blockchain
		6.4.2 The components of a blockchain
		6.4.3 The components of blockchain block
		6.4.4 The blockchain-based architecture of 5G healthcare
			6.4.4.1 Blockchain for network function virtualization
			6.4.4.2 Blockchain for software-defined networking
			6.4.4.3 Blockchain for D2D communications
			6.4.4.4 Blockchain for edge computing
			6.4.4.5 Blockchain for cloud computing
	6.5 Comparative analysis: traditional vs. blockchain-based architecture of 5G healthcare
		6.5.1 Healthcare requirements
			6.5.1.1 Security system
			6.5.1.2 Interoperability
			6.5.1.3 Data sharing
			6.5.1.4 Mobility
		6.5.2 5G opportunities for healthcare requirements
		6.5.3 Blockchain opportunities for healthcare requirements
			6.5.3.1 Simplification of the network
			6.5.3.2 Security improvement
			6.5.3.3 System performance enhancement
		6.5.4 Blockchain to support 5G healthcare architecture functions
			6.5.4.1 5G Healthcare architecture performance enhancement
			6.5.4.2 Security
			6.5.4.3 Privacy
			6.5.4.4 Resource management
			6.5.4.5 Spectrum management
			6.5.4.6 Interference management
		6.5.5 Blockchain-based 5G healthcare architecture use cases
			6.5.5.1 Secured and distributed medical database
			6.5.5.2 Trace medical products to detect counterfeit products.
			6.5.5.3 Telemedicine and medical experience.
	6.6 Conclusion
	References
7 Integrating blockchain technology in 5G-enabled smart healthcare: a SWOT analysis
	7.1 Introduction
		7.1.1 Motivation of the chapter
		7.1.2 Contribution of the chapter
		7.1.3 Organization of the chapter
	7.2 Overview of blockchain technology
		7.2.1 Blockchain structure
		7.2.2 Key characteristics of blockchain
		7.2.3 Applications of blockchain in healthcare
	7.3 Overview of 5G networks
		7.3.1 Relevance of 5G in the healthcare sector
		7.3.2 Performance driving with 5G
		7.3.3 Advance features of 5G technology
		7.3.4 Potential applications of 5G technologies
	7.4 Potentials of integrating blockchain and 5G technology
	7.5 Perceptual overview of integrating blockchain and 5G technology in the healthcare sector
		7.5.1 Challenges of incorporating 5G and blockchain in the healthcare sector
	7.6 Use case scenario
		7.6.1 Characteristics of mobile application interactions between 5G and blockchain technology for serving the patient requirement
		7.6.2 Challenges arise in mobile application interactions between 5G and blockchain technology for serving the patient requirement
	7.7 SWOT analysis of incorporating blockchain and 5G technologies in the healthcare sector
	7.8 Conclusion
	References
8 Architectural framework of 5G-based smart healthcare system using blockchain technology
	8.1 Introduction
		8.1.1 Overview of blockchain for healthcare
		8.1.2 Need for 5G
		8.1.3 Implication of 5G in healthcare
	8.2 Traditional architecture – SHS using blockchain
		8.2.1 Basic architecture of SHS
			8.2.1.1 UI layer
			8.2.1.2 Communication layer
			8.2.1.3 Backend supporting layer
		8.2.2 Architectural structure of blockchain
			8.2.2.1 Hardware/infrastructure layer
			8.2.2.2 Data layer
			8.2.2.3 Network layer
			8.2.2.4 Consensus layer
			8.2.2.5 Application layer
		8.2.3 SHS architecture using blockchain
	8.3 5G-based smart healthcare architecture using blockchain
		8.3.1 Introduction
		8.3.2 Smart healthcare
		8.3.3 Design objectives of SHS
		8.3.4 5G for SHS
			8.3.4.1 5G
			8.3.4.2 5G features that support SHS
			8.3.4.3 How 5G affects SHS
			8.3.4.4 5G-based SHS architecture
			8.3.4.5 Communication technologies in 5G architecture
				8.3.4.5.1 Massive MIMO technology
				8.3.4.5.2 mmWaves communication technology
				8.3.4.5.3 D2D communication technology
				8.3.4.5.4 Cognitive radio
		8.3.5 Blockchain in smart healthcare
		8.3.6 5G-based architecture for SHS using blockchain
		8.3.7 Smart health devices and their significance
	8.4 Privacy and security in 5G-based SHS
	8.5 Advantages of 5G-based architecture in SHS
	8.6 Open research issues and challenges
	References
9 Application of millimeter wave (mm-Wave)-based device-to-device (D2D) communication in 5G healthcare
	9.1 Introduction
		9.1.1 5G: features
	9.2 Introduction to D2D communication technology
		9.2.1 D2D-assisted cellular communication
		9.2.2 D2D communication in LTE advanced
		9.2.3 Technical aspects of D2D communication
		9.2.4 mmWave for D2D communication
		9.2.5 mmWave communication features
	9.3 Introduction to WBAN
		9.3.1 Wireless personal area network (WPAN)/wireless local area network (WLAN)
		9.3.2 WBAN design requirements
		9.3.3 mmWave in WBAN
	9.4 5G-based internet of medical things
		9.4.1 IoMT architecture
	9.5 Open issues
		9.5.1 Security issues in 5G-D2D-based WBAN
		9.5.2 Propagation losses in mmWave communication
		9.5.3 Impact of mmWave radiations on human health
	9.6 Conclusion
	References
10 Security and privacy in health data storage and its analytics
	10.1 Introduction
		10.1.1 Contribution
		10.1.2 Organization
	10.2 Data analytic in 5G
		10.2.1 Application intelligence
		10.2.2 Network intelligence
		10.2.3 Phases in data analytic
			10.2.3.1 Phase 1
			10.2.3.2 Phase 2
			10.2.3.3 Phase 3
			10.2.3.4 Phase 4
			10.2.3.5 Phase 5
	10.3 Tools for analysis
		10.3.1 Hadoop distributed file system
		10.3.2 Text mining
		10.3.3 Complex event processing
		10.3.4 Hive
		10.3.5 Jaql
		10.3.6 Zookeeper
		10.3.7 Apache solr
		10.3.8 Lucene
		10.3.9 Presto
	10.4 Data storage
		10.4.1 Value
		10.4.2 Variety
		10.4.3 Velocity
		10.4.4 Veracity
		10.4.5 On-premise data storage
		10.4.6 Cloud storage
			10.4.6.1 Relational database MySQL
			10.4.6.2 NoSQL database
			10.4.6.3 Key value store
			10.4.6.4 Document store
			10.4.6.5 Extensible record stores or wide column/column family stores
			10.4.6.6 Graph database
		10.4.7 Hybrid approach
	10.5 Introduction to security and privacy
	10.6 Security threats in a wireless communication system
		10.6.1 Rogue access points
		10.6.2 Denial of service (DoS)
		10.6.3 Configuration problems
		10.6.4 Passive capturing
		10.6.5 1G networks
		10.6.6 2G networks
		10.6.7 3G networks
		10.6.8 4G networks
		10.6.9 5G networks
	10.7 E2E security solution for 5G
	10.8 Privacy challenges in 5G networks
		10.8.1 Loss of data ownership
		10.8.2 Location of legal disputes
		10.8.3 Shared environment
		10.8.4 Hacking
		10.8.5 Providing information for third party
	10.9 Privacy solutions for 5G
		10.9.1 Privacy-aware routing mechanisms by using SDN
		10.9.2 Hybrid cloud approach
		10.9.3 Service-oriented privacy preserving, mechanism
	10.10 Privacy and security concerns in healthcare data
		10.10.1 Importance of security and privacy in healthcare data
		10.10.2 Sharing data in cloud
		10.10.3 Data administration and laws
		10.10.4 Malware attacks
		10.10.5 Medical identity theft
		10.10.6 Social issues
		10.10.7 Incorrect diagnosis and treatment
		10.10.8 Denial of valid insurance claims
		10.10.9 Employment issues
	10.11 Security of healthcare data
		10.11.1 EHR storage
		10.11.2 Malicious code
		10.11.3 Mobile devices
		10.11.4 Online systems protection
		10.11.5 Protected access
		10.11.6 Healthcare data security life cycle
			10.11.6.1 Data collection phase
			10.11.6.2 Data transformation phase
			10.11.6.3 Data modeling phase
			10.11.6.4 Knowledge creation phase
		10.11.7 Technologies used for security of healthcare data
			10.11.7.1 Authentication
			10.11.7.2 Data masking
			10.11.7.3 Encryption
			10.11.7.4 Auditing and monitoring
		10.11.8 Access control
		10.11.9 5GHealthNet
		10.11.10 Healthchain
			10.11.10.1 IoT devices
			10.11.10.2 User nodes
			10.11.10.3 Doctor nodes
			10.11.10.4 Accounting node
			10.11.10.5 Storage nodes
			10.11.10.6 Userchain
			10.11.10.7 Docchain
	10.12 Privacy of healthcare data
		10.12.1 Data protection laws
		10.12.2 HIPAA Act, Patient Safety and Quality Improvement Act (PSQIA), and HITECH Act
		10.12.3 IT Act and IT (Amendment) Act
		10.12.4 Constitution
		10.12.5 Data Protection Act (DPA)
		10.12.6 Data protection directive
		10.12.7 The 09-08 Act, dated 18 February 2009
		10.12.8 Methods of privacy preservation for healthcare data
			10.12.8.1 De-identification
			10.12.8.2 HybrEx
			10.12.8.3 Notice and consent
			10.12.8.4 Micro aggregation
		10.12.9 A privacy framework for healthcare data in cloud computing
	10.13 Conclusion
	References
11 Artificial intelligence and machine learning techniques for diabetes healthcare
	Keywords
	11.1 Introduction
		11.1.1 Research contribution
	11.2 Data science healthcare applications overview
		Predictive
		Diagnostic
		Prescriptive
	11.3 Data science
		11.3.1 Healthcare management and health informatics
		11.3.2 Machine learning
		11.3.3 Deep learning
	11.4 Diabetes mellitus and its complication
	11.5 Deep learning model for prediction of diabetes retinopathy
		11.5.1 Diabetic retinopathy
		11.5.2 Methodology for deep learning model
			11.5.2.1 Image classification using FastAI library
			11.5.2.2 Google Colaboratory
			11.5.2.3 CNN using FastAI
			Step 1: Downloading image data
			Step 2: Load and view data
			Step 3: Create and train a model
			Step 4: Cleaning the data
			Step 5: Interpretation
	11.6 Results and discussion
	11.7 Machine learning model for prediction of diabetes mellitus
		11.7.1 Description of the dataset
		11.7.2 Knowledge base designing
		11.7.3 Knowledge base as a dataset
			11.7.3.1 Methodology
			11.7.3.2 Machine learning model
			11.7.3.3 Libraries and dataset
	11.7.4 Results and discussion
		11.7.5 Prediction tests
	11.8 Conclusion
	References
12 Analytics for data security and privacy in 5G healthcare services
	12.1 Introduction
	12.2 IoMT security and privacy architecture model
		12.2.1 Awareness or perception level
			a) Embedded devices:
			b) Surrounding devices:
			c) Motionless system:
			12.2.1.1 Some of the awareness layer attacks
		12.2.2 Communication layer
			12.2.2.1 Some communication or network layer attacks
		12.2.3 Middleware layer
			12.2.3.1 Some middleware layer attacks
		12.2.4 Software or application layer
			12.2.4.1 Potential strikes in this level are as follows:
	12.3 Suggested taxonomy for IoT-based receptors within the e-health-care system domain
	12.4 Taxonomy of IoT security
		12.4.1 IoT security risk
		12.4.2 Prerequisite
		12.4.3 Institute of electrical and electronics engineers standards
		12.4.4 Deployment level
		12.4.5 Technical knowledge
	12.5 S-health framework and techniques
	12.6 Identified issues and solutions
		12.6.1 Summary of analyzed effort held through this particular research
	12.7 Open issues and challenges
	12.8 Conclusions and open research issues in future
	References
13 Contactless attendance system: a healthcare approach to prevent spreading of Covid-19
	13.1 Introduction
		13.1.1 Traditional attendance system
		13.1.2 Automated attendance system
		13.1.3 Motivation
	13.2 Literature review
		13.2.1 5G and Covid-19 blockchain: value and importance
	13.3 Proposed system
		13.3.1 Student and capture image
		13.3.2 Face detection
		13.3.3 Cropping of faces
		13.3.4 Face recognition
		13.3.5 Database of students’ images
		13.3.6 Record attendance and attendance system
	13.4 Face detection
		13.4.1 Object localization
		13.4.2 Classification with localization
		13.4.3 Landmark detection
	13.5 Object detection
		13.5.1 Training set creation and training
		13.5.2 Sliding window technique
		13.5.3 Fully connected layers to convolutional layers
		13.5.4 Convolution implementation of sliding windows [29]
		13.5.5 Drawing bounding boxes
		13.5.6 Intersection over Union
		13.5.7 Non-max suppression
		13.5.8 Anchor boxes
		13.5.9 Results
	13.6 Face recognition
		13.6.1 Introduction
		13.6.2 Face verification vs. face recognition
		13.6.3 Processes involved in face recognition
		13.6.4 One-shot learning problem
		13.6.5 Recognition model
		13.6.6 Identifying the model
			A simple model
			A better model
			The best model
		13.6.7 Training the model—triplet loss [20]
			Triplet loss
		13.6.8 Encoding faces
		13.6.9 Results
		13.6.10 Recording attendance
	13.7 Attendance and visitor management
		13.7.1 Why change?
		13.7.2 Intervention
		13.7.3 Possible demerits
	13.8 Final takeaways
		13.8.1 Face detection
		13.8.2 Image classification and recognition
		13.8.3 Storage of the attendance date and time
		13.8.4 Better system with liveness detection
		13.8.5 Practical usage of the system
		13.8.6 Online database and user interaction
		13.8.7 Communicating with the user
	13.9 Conclusion
	References
14 Blockchain-based smart contracts for e-healthcare management 4.0
	14.1 Introduction
		14.1.1 Evolution of Health care 1.0 to 4.0
		14.1.2 Blockchain in health-care applications used for preventing diseases
			14.1.2.1 Blockchain for drug traceability
			14.1.2.2 Facilitating clinical trials and research
			14.1.2.3 Taxonomy of the paper
	14.2 Related works on blockchain technology in health-care sectors
	14.3 Blockchain-based health-care and management applications
	14.4 Benefits of blockchain technology in the health-care industry
	14.5 Ethereum—system design
	14.6 5G networks and Ethereum for the health-care sector
		14.6.1 Challenges in the health-care sector
	14.7 Real-time examples of Ethereum in the health-care sector
	14.8 5G networks and smart contracts
	14.9 Advantages of smart contracts
	14.10 Choosing the smart contract platform
	14.11 Applications of smart contracts in healthcare
	14.12 Case study—design and architecture
		14.12.1 Client layer
		14.12.2 Blockchain layer
	14.13 System implementation
		14.13.1 Smart contracts
		14.13.2 Algorithm
	14.14 Experimental setup
		14.14.1 Performance evaluation
			14.14.1.1 Transaction data
			14.14.1.2 Evaluation of measurements
	14.15 Results
	14.16 Conclusion
	References
15 An amalgamation of blockchain, Internet of Medical Things and 5G technologies for the Healthcare 4.0 ecosystem
	15.1 Introduction
		15.1.1 Motivation and significance for the study
		15.1.2 Market potential for the health-care industry
		15.1.3 Overview of blockchain, 5G and IoMT technologies
			15.1.3.1 Blockchain technology
			15.1.3.2 5G network communication
			15.1.3.3 Internet of Medical Things (IoMT)
			15.1.3.4 Integration of 5G, blockchain, and IoMT solutions
			15.1.3.5 Evolution of technological shift from Healthcare 1.0 to Healthcare 4.0
		15.1.4 Organization of the chapter
		15.1.5 Authors’ research contribution
		15.1.6 Taxonomy and acronyms
	15.2 Review of recent literature
		15.2.1 Blockchain
		15.2.2 Survey on web portals and mobile apps literature
		15.2.3 Healthcare 4.0 ecosystem
		15.2.4 IoMT survey
		15.2.5 Comparative analysis of survey papers with specific parameters
		15.2.6 Findings from literature survey
	15.3 Architecture of the Healthcare 4.0 ecosystem
	15.4 Research issues, implementation challenges, and future directions
		15.4.1 Research issues in IoMT and Healthcare 4.0
			15.4.1.1 Patient data management
			15.4.1.2 Scalability
			15.4.1.3 Standardization
			15.4.1.4 Human factors in engineering and interfaces
			15.4.1.5 Security and privacy
			15.4.1.6 Lack of interoperability
			15.4.1.7 Optional feasibility
			15.4.1.8 Regulations
			15.4.1.9 Interdisciplinary
	15.5 A Healthcare 4.0 ecosystem platforms and tools case study
		15.5.1 Qualcomm Life—Capsule
		15.5.2 Phillips HealthSuite
		15.5.3 GDm-Health system for gestational diabetes mellitus
		15.5.4 Medtronic insulin pump
		15.5.5 Medtronic CareLink
	15.6 Conclusion
	References
16 Detection of COVID-19 and its symptoms using chest X-rays for health care
	16.1 Introduction
		16.1.1 Motivation
		16.1.2 Importance of blockchain in 5G and COVID-19
		16.1.3 Research contributions
		16.1.4 Organization of the chapter
	16.2 Objective
	16.3 Literature review
		16.3.1 Current methodology
		16.3.2 Related work
	16.4 Theoretical background
		16.4.1 Technologies used
			16.4.1.1 Python
			16.4.1.2 OpenCV
			16.4.1.3 Keras
			16.4.1.4 TensorFlow
			16.4.1.5 Scikit-learn
			16.4.1.6 Scikit-image
			16.4.1.7 Dlib
			16.4.1.8 MXNet
			16.4.1.9 imutils
			16.4.1.10 Kaggle
			16.4.1.11 GitHub
			16.4.1.12 Convolutional neural networks
			16.4.1.13 Conceptual model
	16.5 Experimental analysis
		16.5.1 Importing the dataset
		16.5.2 Pre-processing of the data
		16.5.3 Splitting the training and test data
		16.5.4 Architecture of CNN
		16.5.5 Callbacks
		16.5.6 Fitting model
		16.5.7 Graphical plot of accuracy and loss function
	16.6 Results and discussion
	16.7 Blockchain for integration with 5G networks and handling COVID-19
	16.8 Research opportunities and open issues
	16.9 Conclusion and future scope
	References
17 Security and privacy control in 5G-enabled health care using blockchain
	17.1 Introduction
		17.1.1 Motivation
		17.1.2 Contribution
		17.1.3 Organization
	17.2 Background theory
		17.2.1 Smart health care
		17.2.2 5G
		17.2.3 5G-enabled SH
		17.2.4 Blockchain technology
		17.2.5 Evolution of blockchain
		17.2.6 Blockchain for 5G-enabled health care
	17.3 Current issues and challenges in 5G-enabled health care
		17.3.1 Technological challenges
		17.3.2 Common challenges
	17.4 Security and privacy concerns in 5G-enabled health care
	17.5 Existing blockchain-based security solutions for health care
		17.5.1 Challenges of blockchain with 5G-enabled SH
	17.6 Conclusion
	References
18 M2M for health care with blockchain security aspects
	18.1 Introduction
	18.2 State of the art: blockchain and M2M
		18.2.1 Background of the M2M network
		18.2.2 Background of blockchain
		18.2.3 Integration of blockchain and M2M
		18.2.4 Literature survey/related work
	18.3 Blockchain for M2M-enabling technologies
		18.3.1 Communication blockchain design in the public network area
		18.3.2 Communication blockchain design in the private network area
	18.4 Challenges and proposed solutions of M2M
		18.4.1 Physical random access channel (PRACH) overload problem
		18.4.2 Inefficient radio resource utilization and allocation
		18.4.3 Clustering techniques
		18.4.4 QoS provisioning for M2M device communication
		18.4.5 Cheap price and low power requirements for devices
		18.4.6 Security and privacy
	18.5 M2M implementation in health-care—a future direction
		18.5.1 Predictive maintenance of medical devices by employing M2M
		18.5.2 Intelligent manufacturing by M2M
		18.5.3 M2M creates smart hospitals
		18.5.4 M2M provisions automatic alerting systems
		18.5.5 Emergency medical services possible via M2M
		18.5.6 Remote vital sign monitoring from a hospital environment through M2M
		18.5.7 Post-marketing surveillance of medical devices
		18.5.8 Security and interoperability in health care
		18.5.9 Use cases of blockchain-based M2M-enabled health-care applications
	18.6 Conclusion
	References
Index
Back Cover