Blockchain and Deep Learning for Smart Healthcare
Description
The book discusses the popular use cases and applications of blockchain technology and deep learning in building smart healthcare.
The book covers the integration of blockchain technology and deep learning for making smart healthcare systems. Blockchain is used for health record-keeping, clinical trials, patient monitoring, improving safety, displaying information, and transparency. Deep learning is also showing vast potential in the healthcare domain. With the collection of large quantities of patient records and data, and a trend toward personalized treatments. there is a great need for automated and reliable processing and analysis of health information. This book covers the popular use cases and applications of both the above-mentioned technologies in making smart healthcare.
Audience
Comprises professionals and researchers working in the fields of deep learning, blockchain technology, healthcare & medical informatics. In addition, as the book provides insights into the convergence of deep learning and blockchain technology in healthcare systems and services, medical practitioners as well as healthcare professionals will find this essential reading.
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Persons
Akansha Singh, PhD, is an associate professor in the School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India. Dr. Singh has acquired a BTech, MTech, and PhD (IIT Roorkee) in the area of neural networks and remote sensing. She has to her credit more than 70 research papers, 20 books, and numerous conference papers. She has also national and international patents in the field of machine learning. Her area of interest includes mobile computing, artificial intelligence, machine learning, and digital image processing.
Anuradha Dhull, PhD, is an assistant professor in the Department of Computer Science Engineering, The NorthCap University, Gurugram, India. She has published more than 30 research papers in the area of data mining and machine learning. Dr. Anuradha has acquired a BTech, MTech, and PhD in the area of medical diagnosis and machine learning.
Krishna Kant Singh, PhD, is a professor at the Delhi Technical Campus, Greater Noida, India. Dr. Singh has acquired a BTech, MTech, and PhD (IIT Roorkee) in the area of deep learning and remote sensing. He has authored more than 80 technical books and research papers in international conferences and SCIE journals of repute.
Content
Preface xv
Part 1: Blockchain Fundamentals and Applications 1
1 Blockchain Technology: Concepts and Applications 3
Hermehar Pal Singh Bedi, Valentina E. Balas, Sukhpreet Kaur and Rubal Jeet
1.1 Introduction 3
1.2 Blockchain Types 4
1.3 Consensus 8
1.4 How Does Blockchain Work? 10
1.5 Need of Blockchain 12
1.6 Uses of Blockchain 12
1.7 Evolution of Blockchain 14
1.8 Blockchain in Ethereum 17
1.9 Advantages of Smart Contracts 21
1.10 Use Cases of Smart Contracts 21
1.11 Real-Life Example of Smart Contracts 22
1.12 Blockchain in Decentralized Applications 22
1.13 Decentraland 25
1.14 Challenges Faced by Blockchain 27
1.15 Weaknesses of Blockchain 29
1.16 Future of Blockchain 30
1.17 Conclusion 31
2 Blockchain with Federated Learning for Secure Healthcare Applications 35
Akansha Singh and Krishna Kant Singh
2.1 Introduction 36
2.2 Federated Learning 36
2.3 Motivation 37
2.4 Federated Machine Learning 38
2.5 Federated Learning Frameworks 39
2.6 FL Perspective for Blockchain and IoT 39
2.7 Federated Learning Applications 41
2.8 Limitations 42
3 Futuristic Challenges in Blockchain Technologies 45
Arun Kumar Singh, Sandeep Saxena, Ashish Tripathi, Arjun Singh and Shrikant Tiwari
3.1 Introduction 46
3.2 Blockchain 47
3.3 Issues and Challenges with Blockchain 53
3.4 Internet of Things (IoT) 58
3.5 Background of IoT 59
3.6 Conclusion 67
4 AIML-Based Blockchain Solutions for IoMT 73
Rishita Khurana, Manika Choudhary, Akansha Singh and Krishna Kant Singh
4.1 Introduction 74
4.2 Objective and Contribution 75
4.3 Security Challenges in Different Domains 76
4.4 Healthcare 77
4.5 Agriculture 77
4.6 Transportation 78
4.7 Smart Grid 78
4.8 Smart City 78
4.9 Smart Home 79
4.10 Communication 79
4.11 Security Attacks in IoT 81
4.12 Solutions for Addressing Security Using Machine Learning 83
4.13 Solutions for Addressing Security Using Artificial Intelligence 83
4.14 Solutions for Addressing Security Using Blockchain 86
4.15 Summary 88
4.16 Critical Analysis 89
4.17 Conclusion 89
5 A Blockchain-Based Solution for Enhancing Security and Privacy in the Internet of Medical Things (IoMT) Used in e-Healthcare 95
Meenakshi and Preeti Sharma
5.1 Introduction: E-Health and Medical Services 96
5.2 Literature Review 98
5.3 Architecture of Blockchain-Enabled IoMT 101
5.4 Proposed Methodology 104
5.5 Conclusion and Future Work 108
6 A Review on the Role of Blockchain Technology in the Healthcare Domain 113
Aryan Dahiya, Anuradha, Shilpa Mahajan and Swati Gupta
6.1 Introduction 113
6.2 Systematic Literature Methodology 119
6.3 Applications of Blockchain in the Healthcare Domain 122
6.4 Blockchain Challenges 136
6.5 Future Research Directions and Perspectives 139
6.6 Implications and Conclusion 140
7 Blockchain in Healthcare: Use Cases 147
Utsav Sharma, Aditi Ganapathi, Akansha Singh and Krishna Kant Singh
7.1 Introduction 147
7.2 Challenges Faced in the Healthcare Sector 149
7.3 Use Cases of Blockchains in the Healthcare Sector 150
7.4 What is Medicalchain? 159
7.5 Implementing Blockchain in SCM 165
7.6 Why Use Blockchain in SCM 167
Part 2: Smart Healthcare 171
8 Potential of Blockchain Technology in Healthcare, Finance, and IoT: Past, Present, and Future 173
Chetna Tiwari and Anuradha
8.1 Introduction 173
8.2 Types of Blockchain 175
8.3 Literature Review 177
8.4 Methodology and Data Sources 188
8.5 The Application of Blockchain Technology Across Various Industries 189
8.6 Conclusion 199
9 AI-Enabled Techniques for Intelligent Transportation System for Smarter Use of the Transport Network for Healthcare Services 205
Meenakshi and Preeti Sharma
9.1 Introduction 206
9.2 Artificial Intelligence 208
9.3 Artificial Intelligence: Transport System and Healthcare 209
9.4 Artificial Intelligence Algorithms 211
9.5 AI Workflow 215
9.6 AI for ITS and e-Healthcare Tasks 216
9.7 Intelligent Transportation, Healthcare, and IoT 218
9.8 AI Techniques Used in ITS and e-Healthcare 221
9.9 Challenges of AI and ML in ITS and e-Healthcare 223
9.10 Conclusions 225
10 Classification of Dementia Using Statistical First-Order and Second-Order Features 235
Deepika Bansal and Rita Chhikara
10.1 Introduction 236
10.2 Materials and Methods 238
10.3 Proposed Framework 239
10.4 Experimental Results and Discussion 247
10.5 Conclusion 251
11 Pulmonary Embolism Detection Using Machine and Deep Learning Techniques 257
Renu Vadhera, Meghna Sharma and Priyanka Vashisht
11.1 Introduction 257
11.2 The State-of-the-Art of PE Detection Models 260
11.3 Literature Survey 261
11.4 Publications Analysis 270
11.5 Conclusion 270
12 Computer Vision Techniques for Smart Healthcare Infrastructure 277
Reshu Agarwal
12.1 Introduction 278
12.2 Literature Survey 280
12.3 Proposed Idea 308
12.4 Results 316
12.5 Conclusion 317
13 Energy-Efficient Fog-Assisted System for Monitoring Diabetic Patients with Cardiovascular Disease 323
Rishita Khurana, Manika Choudhary, Akansha Singh and Krishna Kant Singh
13.1 Introduction 324
13.2 Literature Review 326
13.3 Architectural Design of the Proposed Framework 328
13.4 Fog Services 330
13.5 Smart Gateway and Fog Services Implementation 337
13.6 Cloud Servers 338
13.7 Experimental Results 339
13.8 Future Directions 345
13.9 Conclusion 350
14 Medical Appliances Energy Consumption Prediction Using Various Machine Learning Algorithms 353
Kaustubh Pagar, Tarun Jain, Horesh Kumar, Aditya Bhardwaj and Rohit Handa
14.1 Introduction 354
14.2 Literature Review 355
14.3 Methodology 356
14.4 Machine Learning Algorithms Used 364
14.5 Results and Analysis 368
14.6 Model Analysis 369
14.7 Conclusion and Future Work 374
Part 3: Future of Blockchain and Deep Learning 379
15 Deep Learning-Based Smart e-Healthcare for Critical Babies in Hospitals 381
Ritam Dutta
15.1 Introduction 382
15.2 Literature Survey 383
15.3 Evaluation Criteria 392
15.4 Results 393
15.5 Conclusion and Future Scope 394
16 An Improved Random Forest Feature Selection Method for Predicting the Patient's Characteristics 399
K. Indhumathi and K. Sathesh Kumar
16.1 Introduction 400
16.2 Literature Survey 402
16.3 Dataset 403
16.4 Data Analysis 406
16.5 Data Pre-Processing 407
16.6 Feature Selection Methods 408
16.7 Variable Importance by Machine Learning Methods 414
16.8 Random Forest Feature Selection 415
16.9 Proposed Methodology 418
16.10 Results and Discussion 420
16.11 Conclusion 421
17 Blockchain and Deep Learning: Research Challenges, Open Problems, and Future 425
Akansha Singh and Krishna Kant Singh
17.1 Introduction 426
17.2 Research Challenges 427
17.3 Open Problems 428
17.4 Future Possibilities 429
17.5 Conclusion 430
References 431
Index 433
1
Blockchain Technology: Concepts and Applications
Hermehar Pal Singh Bedi1*, Valentina E. Balas2, Sukhpreet Kaur1 and Rubal Jeet1
1Department of Computer Science and Engineering, Chandigarh Engineering College, Landran, Mohali, Punjab, India
2Department of Automatics and Applied Software, University of Arad, Arad Romania
Abstract
Many new technologies evolve and deplete over time, but the most significant technological innovation in recent years has been blockchain technology, which not only has changed almost all aspects of life but also could incorporate all the existing technologies. In this chapter, we will be elaborating all the concepts of blockchain technology and try to understand its purpose in today's world. We will also look into its use cases especially from a security point of view. As we delve a bit more into the details, we will be looking into the workings of blockchain technology, the different types of blockchains available depending on the network and the consensus mechanism, its structure, and the opportunities for blockchains. Lastly, we will also be exploring some of the challenges that blockchain is facing due to public perception and also the future prospects of blockchain technology.
Keywords: Blockchain, cryptocurrency, smart contracts, decentralized applications
1.1 Introduction
The proposal of a protocol similar to that of blockchain was proposed by cryptographer David Chaum in his dissertation "Computer Systems Established, Maintained, and Trusted by Mutually Suspicious Groups" in 1982 [1]. In 1991, researchers Haber et al. and Stornetta et al. have illustrated the algorithms on a secured chain of blocks very effectively using cryptography [2, 3]. Nakamoto et al. introduced the method of decentralized blockchain in 2008. He used blockchain for all the transactions made on the Bitcoin network using a ledger in a public domain. Originally, Satoshi Nakamoto used the words "block" and "chain" as two different words, but later were combined to make a single word, "blockchain".
Blockchain technology is interpreted by many IT professionals as the biggest innovative technological research in today's digital world in terms of secured assets. Blockchain is the technique of sharing the ledger, which is also one of the best techniques of decentralization of both catalogs and accounts on big data [4]. It is a shared and immutable, i.e., unchangeable and incorruptible, ledger that clears the path for the procedure of documenting the transactions made and tracking the different transactions and assets of any network related to any business. Assets can be of two types: tangible and intangible.
- Tangible assets: These are the physical assets that can be touched such as property, money, vehicles, etc.
- Intangible assets: These are the assets that do not exist in real life but have real-life monetary value such as the crypto-currency, patents, trademarks, etc.
When the defined network is decentralized, then different nodes are used to write, share, and lock the consistent transactions in a distributed ledger [5]. Blockchain works similarly, with the difference being that the data in blockchain are organized into chronological and cryptographical linked blocks, and it also uses different types of mechanisms based on consensus and smart contracts [6].
1.2 Blockchain Types
Broadly, there are four types of blockchains available, which are shown in Figure 1.1.
Figure 1.1 Types of blockchains available.
- Public blockchains are the blockchains that do not require any permissions and are not managed by any company or individual. In public blockchains, anyone can become the node. Public blockchains are purely decentralized and hence allows equal access of blockchains to each and every node. Moreover, each node has the right to create and validate a block of data. There are different blockchains available in the public domain, including Bitcoin, Ethereum, and Litecoin. Mostly, the public blockchains are used for exchanging and mining cryptocurrencies. Public blockchains are criticized by many because of security reasons as the information in the public domain can be accessed by anyone joining the network [7]. In public blockchains, all the nodes are treated equally and none of the nodes available on the network have any special privileges. We can interchangeably use permissionless and public blockchain [8]. The public blockchain features access in real-life examples [9].
- Private blockchains or managed or permissioned blockchains are blockchains that require some permissions, which are managed or controlled by some company or an individual. In managed blockchains, the company or the individual who owns the blockchain grants permissions and makes the decision in creating the nodes. It is not necessary that each node enjoys the same rights similar to public blockchains. They are not purely decentralized as not all the information is available to the public. Ripple and Hyperledger are the examples of permissioned or managed blockchain technologies available. The terms "permissioned" and "private" are used interchangeably [8]. All the nodes in this blockchain have different rights for using the services of the network, which includes data accessing, reading, and making transactions, all limited to an individual or some company. The use cases of private blockchains have been increasing [8].
- Consortium blockchain is a managed and permissioned blockchain that is managed by a group of organizations rather than an individual. Consortium blockchain is more decentralized as compared to private blockchain, which results in high security. Consortium blockchain is mostly used in the financial services industry and supply chain sectors. Quorum and Corda are examples of consortium blockchains. In a consortium blockchain, all the nodes have different rights for using the services of the network, and it is all limited to the company.
- Hybrid blockchain is a singly managed blockchain, which also requires the oversight of some other public blockchains for the validation of transactions. Transactions made in hybrid blockchains are kept private, which can be verified whenever required by enabling access through a smart contract. A hybrid blockchain allows organizations to establish a private and secured system that requires permissions alongside a public permissionless system, which enables them to administer and decide about the level of rights to be given to each member for accessing the data. Either it can be made private with restricted rights or it can be made public [10]. XinFin is an example of a hybrid blockchain.
Some of the papers also divide the blockchain into only two types, depending on their architecture:
- Permissioned
- Permissionless
Permissioned blockchains include the blockchain networks, in which all the nodes do not have the right to access, read, write, and transact, but all these facilities are limited to some company or individual. Permissioned blockchains include both private and consortium blockchains discussed above and are also sometimes referred to as private blockchains [8]. They use QuorumChain and majority voting consensus, because of which they are faster than permissionless blockchains [11]. Permissioned blockchains are comparatively more secured than public or permissionless blockchains as not all the nodes can access the data available on the network.
Figure 1.2 Types of blockchains.
Table 1.1 Comparison of different blockchains [13].
Property Public blockchain Private blockchain Consortium blockchain Consensus determination All different nodes in the network Only limited to one network of company Only selected nodes Type: Permissionless/Permissioned Permissionless Permissioned Permissioned Security Secured as it is immutable. Less secured as it is mutable and can be tempered. Less secured as it is mutable and can be tempered. Identity Anonymous identity [12] Known identity of users [12] Known identity of users [12] Consensus Type Proof of work QuorumChain QuorumChain and majority votingPermissionless blockchains include the blockchain networks, in which all the nodes are treated equally, have access to all the information on the network, and can broadcast the transaction on the network. Public blockchains include the public blockchain discussed above and are also sometimes referred to as permissionless blockchains [8]. It uses proof-of-work (PoW) consensus, which ensures that all the nodes are only permitted to take any decision if they reach consensus. This also has an adverse effect of slowing down the network [11].
Thus, the types of blockchains available can be classified into two types and then further divided into subtypes as shown in Figure 1.2.
The differences between different types of blockchains...
