Next Article in Journal
Difference of Two Antiseptic Gels for the Treatment of Peri-Implant Mucositis on Plaque Index and Bleeding Score: A Randomized Controlled Clinical Study
Next Article in Special Issue
Evaluation of the Machinability of Ti-6Al-4V Titanium Alloy by AWJM Using a Multipass Strategy
Previous Article in Journal
Influence of Atmospheric Flow Structure on Optical Turbulence Characteristics
Previous Article in Special Issue
Visual Simulator for Mastering Fundamental Concepts of Machine Learning
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Blockchain-Based Internet of Medical Things

Department of Arts, Communications and Social Sciences, University Canada West, Vancouver, BC V6B 1V9, Canada
Appl. Sci. 2023, 13(3), 1287; https://doi.org/10.3390/app13031287
Submission received: 9 December 2022 / Revised: 13 January 2023 / Accepted: 16 January 2023 / Published: 18 January 2023

Abstract

:
IoMT sensor nodes, Internet of Things (IoT) wearable medical equipment, healthcare facilities, patients, and insurance firms are all increasingly being included in IoMT systems. Therefore, it is difficult to create a blockchain design for such systems, since scalability is among the most important aspects of blockchain technology. This realization prompted us to comprehensively analyze blockchain-based IoMT solutions developed in English between 2017 and 2022. This review incorporates the theoretical underpinnings of a large body of work published in highly regarded academic journals over the past decade, to standardize evaluation methods and fully capture the rapidly developing blockchain space. This study categorizes blockchain-enabled applications across various industries such as information management, privacy, healthcare, business, and supply chains according to a structured, systematic evaluation, and thematic content analysis of the literature that is already identified. The gaps in the literature on the topic have also been highlighted, with a special focus on the restrictions posed by blockchain technology and the knock-on effects that such restrictions have in other fields. Based on these results, several open research questions and potential avenues for further investigation that are likely to be useful to academics and professionals alike are pinpointed.

1. Introduction

Securely recovering and correctly managing the amount of individual health data created by delivering service operations and normal business is a major challenge for the healthcare industry. Most of the health data is not easy to access or standardized across systems, and is difficult to interchange, utilize, and understand. They are compiled from several locations and stored in centralized information technology systems, making them challenging to share and administer. Time and energy are required to synthesize, receive, send, and request medical information [1]. Safe data retrieval and management enable healthcare systems to improve health outcomes, communication, treatment quality, and patient views in their entirety [2].
Legacy systems are notorious for being incompatible with newer technologies and for only being able to communicate with other healthcare and medical systems on a limited scale. Data shows various advantages of integrating these networks for better and linked healthcare; however, researchers in health informatics should consider interconnection across different companies [3]. One of the biggest challenges in this area is multi-organizational data sharing, which requires healthcare providers to make their patients’ medical records freely accessible to other organizations, including research or physician institutions [4].
Given the present state of affairs, comprehensive reform of the universal healthcare system is necessary. Historically, medical professionals have handled their evaluations, documentation, and reports on patients and any necessary adjustments to their treatments [5]. With longer life expectancies and a growing world population, a more powerful tool is required for population control. The Internet of Things (IoT) or other decentralized platforms may be employed in this context for achieving dispersed coverage [6]. In light of this, healthcare systems are a crucial IoT application [7,8].
Internet of Medical Things (IoMT) is the kind of IoT that is used in the healthcare industry [9]. IoMTs are the wave of the future in healthcare since they will enable the connectivity and remote monitoring of all medical equipment [10]. Due to these developments, healthcare may now be provided more rapidly and at a lower cost [11]. Medical workers (nurses, physicians, etc.), medical data servers, and medical sensor equipment make up the bulk of an IoMT system that provides remote healthcare [12,13].
There is a long way to go before IoMT can be utilized widely. Most implanted and wearable medical sensor devices lack the computational power and battery life to make complex encryption schemes practical. This means that wireless data transport in the IoMT is open to external attacks [14]. Due to the sensitive nature of patient information included in medical records, it is important to realize that only authorized parties have access to these records [15]. Poor IoMT interoperability [16] is also a problem because of the wide range of medical sensor devices that are available [17] and the diversity of IoMT networks.
The integration of blockchain with IoMT may address the above issues [16,18]. Blockchain is defined by its specific openness, traceability, dependability, and decentralization features. Thus, blockchain technology may be able to address concerns with compatibility, confidentiality, and safety [19]. Blockchain makes it possible for parties who do not trust each other to nevertheless complete a variety of network transactions. Data from a distributed network of devices may be stored and tracked in a blockchain [20]. To the best of our knowledge, this systematic review offers a general overview of the present state, significance, and future of blockchain-based IoMTs, which has not been executed previously.
The structure of the current investigation is as follows: The research methodology that was used to search, filter, and choose the literature is described in detail in Section 2. The third section includes an important review of works that have been undertaken in the area of IoMT using blockchain and summarizes all the papers that have been chosen, concentrating on their primary results and indicating research needs for future studies. The last section of the paper concludes the results.

2. Research Methodology

2.1. Prior Reviews

While blockchain is still a new field of research, several literature evaluations have already been conducted on the topic and its potential uses. In addition, some studies zero in on certain problems in one particular field of application. A review entails the following phases: preparation, execution, identification of core research questions, formulation of search criteria, identification of data sources, and presentation of findings. Detailed examples of each of these stages may be found in the following subsections.

2.2. Planning the Review

This systematic review aims to establish the present standing of blockchain in the IoMT. This investigation was conducted with due diligence by thoroughly reviewing the relevant literature published in the present situation. Structured research questions, databases, and methods for locating and analyzing evidence are all part of the review process. Characteristics of the recommended items in reporting for conducting systematic reviews have been selected to provide a clear, quantitative, and thorough assessment of existing applications in healthcare based on blockchain technology and IoMT. The following points are the main phases in the overall plan:
Recognizing the necessity for conducting an analysis, generating a review proposition, and creating a review.
Finding the appropriate research and studies.
Results overview of the investigation.

2.3. Research Questions

This study aims to organize and describe the present body of research on blockchain and IoMT development, as well as the existing uses of these technologies. Since this study needed to be structured, a set of research questions was developed. Listed below are the specific study topics and their associated sub-questions:
RQ1 (Research Question 1): Where do blockchain-based IoMT systems now stand?
RQ2 (Research Question 2): How important are blockchain applications in the IoMT?
RQ3 (Research Question 3): What is the future of blockchain-based IoMT?

2.4. Research Strategy

A full examination of the literature calls for an all-encompassing perspective. To increase the possibility of finding highly relevant publications, an appropriate selection of databases was chosen before the research was even begun. During the review, the following Scopus sources were explored.

2.5. Search Criteria

To ensure that the research presented here is comprehensive, a thorough search of relevant databases was conducted. However, for a variety of reasons, not all of the canonical literary works have been included in the specified search criteria. About 144 Scopus results have been analyzed until 30 October 2022. Among them, about 73 were determined to be relevant (Figure 1).
The research domain and research questions informed the construction of the search string. By searching for the terms “Blockchain”, “Block chain”, “IoMT” or “Internet of Medical Things,” the essential literature was identified and retrieved.
Inclusion criteria (IC).
  • Research may have been published at any point from 2017 to 2022.
  • Research is confined to the journal.
Exclusion criteria (EC).
  • Papers that are not in English.
  • Reviews, conferences, book chapters, periodicals, theses, monographs, and interview-based pieces are eliminated.

3. Analysis

Results from answering the research questions presented in the previous systematic review are listed in this section. This study seems to make a substantial contribution to the use of blockchain in the medical field. This part introduces blockchain-based IoMT and covers its fundamentals, different varieties, development teams, platforms, and consensus processes. The importance of using blockchain and IoMT in healthcare is discussed further on.

3.1. Selection Results

This search returned 144 results, of which 71 were deemed suitable for screening. This systematic review consists of 73 research papers. Some articles in press met the inclusion criteria but they were not considered in the range of 2017–2022. Following is a list of chosen publications with explanations of the overall classification findings.
RQ1: Where do blockchain-based IoMT systems now stand?
This systematic study examines the attained descriptive data on the several articles published every year, the publishing source, and the annual average number of citations received by research papers. To conclude this systematic review, blockchain-related IoMT research articles published in the area of blockchain between 2017 and 2022 are investigated. Table 1 displays the amount of cited research publications according to their respective periodicals.
From 2017 to 2022, Figure 1 depicts the number of publications produced by topic area. The main subject areas are computer science (65 articles) and engineering (36 articles), mathematics (12 articles), biochemistry, genetics and molecular biology (11 articles), materials science (11 articles), physics and astronomy (10 articles), chemistry (8 articles), medicine (4 articles), etc., respectively. About 39% of research is dedicated to computer science, a unique feature of blockchain and IoMT fundamentals. The next category is engineering (about 22%), which can usefully cover all these subjects.
Figure 2 shows the number of publications published between 2017 and 2022. There is no content from 2017 to 2019. In 2019, two papers were published, while in 2020, six articles were published. The evident anomaly exists between 2020 and 2021. In 2021, 29 articles were published, whereas, in 2022, 36 papers were published. The number of papers published has increased throughout the years. This indicates the concept of integrating IoMT with blockchain has taken shape and expanded over the past four years.
In addition, the examination of author-indexed terms using a word cloud revealed that the focus of the articles was on “blockchain,” “IoMT,” “health care,” “security,” “digital storage,” and “privacy,” as shown graphically in Figure 3. This shows that blockchain and IoMT can be integrated for benefits such as privacy, healthcare, security, and digital storage.
RQ2: How important are blockchain applications in the IoMT?
IoMT has significant benefits for human health, including improved quality of life and reduced healthcare costs [13]. The healthcare industry stands to save as much as USD 300 billion annually if it adopts IoMT devices, notably for telemedicine and chronic diseases. Investing in the IoMT is lucrative since it brought in USD 28 billion in 2017 and is projected to bring in USD 135 billion by 2025 [21]. Key elements, as shown in Figure 4, are wireless sensors that may be used to perform remote monitoring of patient’s health states and communication technologies to relay that data to healthcare providers.
Because of its sensitivity, volume, and importance, medical data requires rigorous guarding [22]. Furthermore, blockchain technology is paving the way for innovative approaches to healthcare data management, access control, sharing, retrieval, storage, and more [23]. Now that blockchain technology is introduced, researchers are more focused on employing blockchain strategies to ensure the security of applications in healthcare [24]. IoMT problems emerged as soon as IoT systems started incorporating medical devices. The lack of consistency is a major barrier. The extensive application of blockchain technology in healthcare is expected to bring along a rise to new “smart” healthcare provider applications that sidestep the latest medical research and create individualized pathways to address the situations [25]. The same level of access to information will be provided for both the patient and the healthcare professionals allowing them to engage in a productive dialogue based on hard facts about the best course of therapy for the patient’s illness [26,27].
Several recent studies have focused on the potential of blockchain technology in the healthcare sector [28,29,30,31,32]. Blockchain technology has made a significant impact on the healthcare sector in terms of transforming digitally in recent years. Blockchain applications for healthcare data management facilitate the regulation of patient record access, the handling of payments and claims, the protection of IoMT [33], and the verification and exchange of research results for financial audits [34] and transparency. To handle, analyze, and make sense of patient health data, the main features of blockchain, including encrypted and distributed ledgers that are updated in real time, are employed [35]. Conceptually, there are layers to access technologies that are new in the blockchain-based healthcare area including healthcare applications, stakeholders, data sources, and blockchain technology [36]. Daisuke et al. [37] employed Hyperledger fabric blockchain technology to transport medical data to the Hyperledger blockchain network, with a particular emphasis on medical records. Telephones were used to collect medical records. The goal of their work was to use the blockchain to record medical records.
There are a number of different approaches in which blockchain technology might improve healthcare for patients, doctors, and scientists [38]. The benefits of customized and research treatment will be maximized by establishing granular data access rights, monitoring individualized data in real-time, and building a central repository for all health data [39]. To better manage healthcare data, Anuraag et al. [40] looked at blockchain technology. They considered a wide range of articles for their research; much of it speculated about the advantages and disadvantages of using blockchain technology in the healthcare industry without providing proof or a system evaluation. The group has finished debating whether or not blockchain technology is more suitable than existing solutions for managing patients’ health information in the cloud without compromising patient confidentiality. When it comes to healthcare management, Khezr et al. [41] found several problems that may be solved with the use of blockchain technology. They highlighted the current research on the application of distributed ledger technology in healthcare and numerous prospective medical applications where blockchain technology may play a critical role in improving efficiency. They also proposed a way for delivering IoMT over existing network infrastructure.
Researchers in the healthcare field are reliant on large sets of data to construct tailored therapies that are based on lifetime, the environment, and genetics, promptly monitoring the development of novel pharmaceuticals, accelerating biomedical discovery, and expanding understanding of the condition [42]. The shared data system in the blockchain would provide a diversified collection of data [43,44] if it included patients from a wide range of ethnic, socioeconomic, and geographical backgrounds. As blockchain records medical information over a person’s whole life, it is well suited for longitudinal studies [45]. Through the use of a healthcare blockchain, those who are underserved by the medical community or who are not generally engaged in research may be included in studies [46]. Because of blockchain’s shared data environment, it is much easier to include formerly difficult-to-reach communities and boost public confidence in the reliability of results [47]. Smart healthcare systems, as can be guessed, need copious amounts of data sharing between medical professionals and their respective tools [48].
A “blockchain” was developed to link all the databases on the network to address this issue. As time goes on, blocks of data are added to a distributed ledger and secured using cryptographic hashing in what is known as a blockchain. Each record includes a cryptographic hash of the previous record to prevent constant unnecessary modifications [49]. A blockchain is recognized by its immutable “ledger,” which implies that once a record is recorded, it cannot be changed in any manner and is available to individuals and under their control. This is the basic aspect of the smart contract system with which the blockchain conforms to the maintenance of one’s identity. Therefore, only licensed medical professionals are allowed to access patient electronic medical records (EMRs) [50]. The “MedBlock” is a blockchain-based information management system that provides immediate EMR access and retrieval [51] thanks to its secure access control and encryption. Vangipuram et al. [52] developed a blockchain implementation and edge architecture called the “Healthcare Data Gateway” (HDG) to ensure the privacy of medical records for COVID-19 patients being transferred to hospitals. To combat the spread of the COVID-19 virus, Alsamhi et al. [53] developed a blockchain setup for a distributed network of robots.
Hassanien et al. [54] used the term “medical of things” to describe the challenges of processing massive volumes of data in the healthcare industry. A related problem is the extraction of intelligent patterns in healthcare data [55]. Medical big data is generated in large quantities by smart IoT devices, making this a potentially life-changing area of study. According to Dey et al. [56], there are many tiers inside the IoT system where sensors are enabled to collect data. This study analyzed the issues occurring at various tiers of the IoT ecosystem. In a similar vein, Kamal et al. [57] investigated the use of a map-reduce architecture to classify medical data in light of preexisting impediments. Another study looked at the need to optimize healthcare data for cloud computing [58].

3.2. Advantages of Using Blockchain-Based Technologies in IoMT Systems

The benefits of employing blockchain technology are outlined below. These include open architecture, trustless consensus, transparency, tamper-proofing, smart contracts, and a distributed ledger [59].
  • The term “open architecture” refers to a kind of technological infrastructure whose developers provide detailed plans for the system. It encompasses both government-sanctioned norms and custom-built structures.
  • Trustless consensus: since distributed consensus is at the heart of blockchain-based IoMT applications, relying on third-party trusted intermediaries such as banks and governments is unnecessary.
  • Transparency: all peers in the network may see all data that is recorded in a block, and the data cannot be modified once it is recorded. To combat problems like counterfeit pharmaceuticals, for instance, it is possible to verify and secure critical drug information by tracking every transaction between drug makers, pharmacists, and patients. The capacity to track where drugs came from will result.
  • Recordings cannot be tampered with, so any attempts to steal or modify patients’ health records are easily uncovered. The dishonest practice of manipulating or altering data from clinical studies, for instance, might be eliminated.
  • In situations where rule-based approaches to patient data access are developed, smart contracts are likely to be utilized to ensure that only authorized parties have access to that data. In this section, authorization for certain medical institutions might be made. Smart contracts may be employed to define the behavior of IoMT applications, automate routine tasks, and provide secure two-way communication and financial transactions between IoMT devices and third parties including patients, and physicians.
  • Because of its decentralized design, the blockchain cannot be hacked or brought down by any one central authority.

3.3. Privacy and Security

Some of the privacy and security benefits that may be realized when a blockchain is integrated with IoMT systems are provided in the following:
  • To ensure that only those who need access to a patient’s medical records do so by the rules put out by the lawful administrator, smart contracts may give access to control property.
  • Each participant in an IoMT system values their privacy and does not want it invaded in any way by the exchange of information. The digital identity of the transactions is used by blockchain to make transactional data unreadable to other parties.
  • CIA (confidentiality, integrity, availability): because the blocks containing data are signed, blockchain provides high levels of integrity protection. In addition, the linking through hashes and the unanimity requirement make it very difficult, if not impossible, to alter the contents inside a block. In addition, a complete version of the data is copied and stored in all nodes, which means a high degree of availability is supplied by construction. However, privacy is compromised due to blockchain’s inbuilt transparency and verifiability checks for every data transaction. Since blockchain implementation focuses more on ensuring the data’s integrity and availability than its secrecy, the latter is less strictly enforced. Since application-level encryption and other techniques where (sensitive) data is not immediately accessible by unauthorized nodes are beyond the purview of this study, the system must offer extra security if a high degree of secrecy is needed [60].
While integrating blockchain and IoMT systems offers security and privacy advantages, serious privacy concerns may occur.

3.4. Blockchain Scalability

Blockchain is an immutable and append-only database that allows for auditable and transparent data management [61]. A hash of the prior block is stored in each block, and the whole structure is implemented as a linked list [62]. The scalability problem is a major issue with blockchain and has been examined at length in [63,64]. The difficulty of scaling blockchain-based Internet of Things applications is addressed in detail in several recent publications [65,66]. Blockchains have scalability issues due to inefficient architecture and consensus procedures [67].
With bitcoin, for instance, the transaction confirmation time is around 10 min, and 7 transactions per second may happen. Companies such as Visa, which handle large volumes of transactions, have a throughput of roughly 24,000 per second. When discussing blockchain scalability, the following metrics are of primary interest [68]:
  • Transaction latency is the time it takes for a payment to be approved. There are other measures, such as bootstrap time and cost per confirmed transaction (CPCT) for the approval process.
  • If you want to know how many transactions per second a blockchain can confirm, you need to know the maximum block size and the average block duration.
This part will explore how blockchain technology is being used for data management in the contexts of the Internet of Things (IoT) and healthcare. It also evaluates the methods that have been taken to combine blockchain technology with the Internet of Things. To illustrate the methods utilized to combine blockchain with IoMT, published papers are also examined. Case studies of blockchain implementations in IoMT are included in Table 2.
RQ3: What is the future of blockchain-based IoMT?
Several substantial research gaps are revealed by the examination of relevant literature. The following problems must be addressed for the future:
I.
The solutions offered are proprietary. They do not create protocols to adapt diverse technology and foster interoperability, preventing their adoption. It is essential to create platform-agnostic, universal solutions that control the interaction between cloud computing, blockchain, IoMT devices, and end users.
II.
Scalability is one of the significant problems that current blockchain-based IoMT applications face, causing slow transaction validation, high transaction fees, high storage memory requirements, and long synchronization times [67,140]. Hence, scalability is an essential factor that needs more research and direction.
III.
The incorporation of blockchain into the IoMT opens the door to several health-related applications. However, the implementation of such technology (blockchain-IoMT) is complex and necessitates in-depth interdisciplinary knowledge, ranging from low-level, such as managing IoMT devices and configuring blockchain to meet IoMT criteria, to high-level knowledge, such as treating, storing, and sharing IoMT data.
IV.
An advancement in personalized medicine, utilizing the most cutting-edge machine learning methods that computer science has to offer, would be made possible by the opportunity of freely sharing sensitive data between experts and health institutions. IoMT gathers huge amounts of information. Finding usable information from the acquired data is a challenge. The IoMT device may provide practical information when using data analytics to examine the data and find flaws, vulnerabilities, and bottlenecks in the system. IoMT data heterogeneity, however, presents difficulties for data analytics [16]. Deep learning advances in machine learning may assist in resolving these issues [141].
V.
The bulk of present works is solely concerned with healthcare applications such as IoMT data management and remote patient monitoring, such as data exchange and storage. Tracking apps that prevent counterfeit medications and medical mishaps are critical. In this context, the adoption of blockchain technology in conjunction with IoMT may be an effective solution for controlling doctor behavior as well as managing the medication supply chain.
Data can be stored in the blockchain’s blocks (which is challenging because of the scalability issues), data provenance can be exploited by storing the locations of data in the blockchains rather than the data itself, and distributed storage can be used in tandem with the blockchain to serve as off-chain storage. The data that could be easily accessed and utilized would never have to be sent over the network in any of the systems.
It is obvious that user-centric solutions are becoming more popular, even if it is not the primary focus of the study. Despite efforts to give consumers more control over their data, developing a truly decentralized system that is user-centric for health data remains a challenge. Authorized systems that are controlled by healthcare institutions are not always clear, since they may provide consumers more control over their data but ultimately need them to comply with consortium norms around data management. Decentralized storages run the danger of being squandered because of this security issue in permissioned systems, which reduces their value. Even in the case that user data is stored in a decentralized manner on the blockchain, this does not ensure a user-centric system if the blockchain might be tampered with by participants. Several actual uses demonstrate this.
If these networks can incentivize users to share personal healthcare data with the community in exchange for benefits, it would be even more astounding if a solution could be found, maybe via hybrid implementations between permissioned and permissionless implementations. No one ever receives credit for the value added by their usage of an IoMT system or an IoT device. In most cases, when people pay for expert assistance, their investment exceeds the results they see. As a matter of fact, in theory, they help advance scientific understanding. Certainly, data sharing and crowdsourcing might be made possible by the Internet of blockchains in a blockchain-enabled society.
To do this, however; it must be shifted from a viewpoint that is rather system-centric, in which a user is just the end consumer of the application, to a user-centric stance, in which a user is an integral part of the design process. A method where each user stores their data locally, as on a smartphone or other portable device, may be quite appealing. If these gadgets serve as secure, distributed storage, then any unknown entity might have easy access to the information kept there, subject to the restrictions set by the users who are the rightful proprietors of the material being shared.

4. Conclusions

A growing number of people are paying attention to the blockchain-based Internet of Medical Things (IoMT) since not only it is likely to reduce healthcare costs but also it can enhance the quality of treatment by relying on continuous and real-time continuous monitoring. IoMT sensor nodes, Internet of Things (IoT) wearable medical devices, patients, healthcare facilities, and insurance companies are just some of the numerous entities that are increasingly being included in IoMT systems. As scalability is one of the key features of blockchain technology, it is challenging to develop a blockchain framework for such systems. This review of blockchain-based IoMT solutions created between 2017 and 2022 was inspired by this insight. The aim is to explore the current state of blockchain technology, the applications it has found, and how its unique features could alter current practices. This study integrates the theoretical foundations of a significant body of work that has been published in prestigious academic publications over the last ten years to standardize assessment techniques and completely capture the blockchain realm, which is quickly evolving. There were 73 papers in the relevant field that are evaluated. Based on a structured, systematic examination and thematic content analysis of the available literature, this research classifies blockchain-enabled applications across a range of sectors, including supply chain, business, healthcare, IoT, privacy, and data management. With a particular emphasis on the limitations presented by blockchain technology and the ripple effects such limitations have in other sectors, the gaps in the literature on the subject have also been emphasized.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The author declares no conflict of interest.

References

  1. Clim, A.; Zota, R.D.; Tinica, G. Big Data in home healthcare: A new frontier in personalized medicine. Medical emergency services and prediction of hypertension risks. Int. J. Healthc. Manag. 2019, 12, 241–249. [Google Scholar] [CrossRef]
  2. Attaran, M. Blockchain technology in healthcare: Challenges and opportunities. Int. J. Healthc. Manag. 2022, 15, 70–83. [Google Scholar] [CrossRef]
  3. Mbunge, E.; Akinnuwesi, B.; Fashoto, S.G.; Metfula, A.S.; Mashwama, P. A critical review of emerging technologies for tackling COVID-19 pandemic. Hum. Behav. Emerg. Technol. 2021, 3, 25–39. [Google Scholar] [CrossRef] [PubMed]
  4. Weber, I.; Xu, X.; Riveret, R.; Governatori, G.; Ponomarev, A.; Mendling, J. Untrusted business process monitoring and execution using blockchain. In International Conference on Business Process Management; Springer: Cham, Switzerland, 2016. [Google Scholar]
  5. Usak, M.; Kubiatko, M.; Shabbir, M.S.; Dudnik, O.V.; Jermsittiparsert, K.; Rajabion, L. Health care service delivery based on the Internet of things: A systematic and comprehensive study. Int. J. Commun. Syst. 2020, 33, e4179. [Google Scholar] [CrossRef]
  6. Pasluosta, C.F.; Gassner, H.; Winkler, J.; Klucken, J.; Eskofier, B.M. An emerging era in the management of Parkinson’s disease: Wearable technologies and the internet of things. IEEE J. Biomed. Health Inform. 2015, 19, 1873–1881. [Google Scholar] [CrossRef]
  7. Farahani, B.; Firouzi, F.; Chakrabarty, K. Healthcare IoT. In Intelligent Internet of Things; Springer: Cham, Switzerland, 2020; pp. 515–545. [Google Scholar]
  8. Wu, J.; Guo, S.; Huang, H.; Liu, W.; Xiang, Y. Information and communications technologies for sustainable development goals: State-of-the-art, needs and perspectives. IEEE Commun. Surv. Tutor. 2018, 20, 2389–2406. [Google Scholar] [CrossRef] [Green Version]
  9. PremaLatha, V.; Sreedevi, E.; Sivakumar, S. Contemplate on internet of things transforming as medical devices-The internet of medical things (IOMT). In Proceedings of the 2019 International Conference on Intelligent Sustainable Systems (ICISS), Palladam, India, 21–22 February 2019; IEEE: Piscataway, NJ, USA, 2019. [Google Scholar]
  10. Adeniyi, E.A.; Ogundokun, R.O.; Awotunde, J.B. IoMT-based wearable body sensors network healthcare monitoring system. In IoT in Healthcare and Ambient Assisted Living; Springer: Singapore, 2021; pp. 103–121. [Google Scholar]
  11. Yeole, A.S.; Kalbande, D.R. Use of Internet of Things (IoT) in healthcare: A survey. In Proceedings of the ACM Symposium on Women in Research 2016, Indore, India, 21–22 March 2016. [Google Scholar]
  12. Habibzadeh, H.; Dinesh, K.; Shishvan, O.R.; Boggio-Dandry, A.; Sharma, G.; Soyata, T. A survey of healthcare Internet of Things (HIoT): A clinical perspective. IEEE Internet Things J. 2019, 7, 53–71. [Google Scholar] [CrossRef]
  13. Awotunde, J.B.; Ogundokun, R.O.; Misra, S. Cloud and IoMT-based big data analytics system during COVID-19 pandemic. In Efficient Data Handling for Massive Internet of Medical Things; Springer: Cham, Switzerland, 2021; pp. 181–201. [Google Scholar]
  14. Rafique, W.; Qi, L.; Yaqoob, I.; Imran, M.; Rasool, R.U.; Dou, W. Complementing IoT services through software defined networking and edge computing: A comprehensive survey. IEEE Commun. Surv. Tutor. 2020, 22, 1761–1804. [Google Scholar] [CrossRef]
  15. Shen, M.; Deng, Y.; Zhu, L.; Du, X.; Guizani, N. Privacy-preserving image retrieval for medical IoT systems: A blockchain-based approach. IEEE Netw. 2019, 33, 27–33. [Google Scholar] [CrossRef]
  16. Dai, H.-N.; Imran, M.; Haider, N. Blockchain-enabled internet of medical things to combat COVID-19. IEEE Internet Things Mag. 2020, 3, 52–57. [Google Scholar] [CrossRef]
  17. Li, X.; Dai, H.-N.; Wang, Q.; Imran, M.; Li, D.; Imran, M.A. Securing internet of medical things with friendly-jamming schemes. Comput. Commun. 2020, 160, 431–442. [Google Scholar] [CrossRef] [PubMed]
  18. Ray, P.P.; Dash, D.; Salah, K.; Kumar, N. Blockchain for IoT-based healthcare: Background, consensus, platforms, and use cases. IEEE Syst. J. 2020, 15, 85–94. [Google Scholar] [CrossRef]
  19. Moin, S.; Karim, A.; Safdar, Z.; Safdar, K.; Ahmed, E.; Imran, M. Securing IoTs in distributed blockchain: Analysis, requirements and open issues. Future Gener. Comput. Syst. 2019, 100, 325–343. [Google Scholar] [CrossRef]
  20. Dilawar, N.; Rizwan, M.; Ahmad, F.; Akram, S. Blockchain: Securing internet of medical things (IoMT). Int. J. Adv. Comput. Sci. Appl. 2019, 10, 82–89. [Google Scholar] [CrossRef] [Green Version]
  21. Ghubaish, A.; Salman, T.; Zolanvari, M.; Unal, D.; Al-Ali, A.; Jain, R. Recent advances in the internet-of-medical-things (IoMT) systems security. IEEE Internet Things J. 2020, 8, 8707–8718. [Google Scholar] [CrossRef]
  22. Al-Janabi, S.; Al-Shourbaji, I.; Shojafar, M.; Shamshirband, S. Survey of main challenges (security and privacy) in wireless body area networks for healthcare applications. Egypt. Inform. J. 2017, 18, 113–122. [Google Scholar] [CrossRef] [Green Version]
  23. Sookhak, M.; Jabbarpour, M.R.; Safa, N.S.; Yu, F.R. Blockchain and smart contract for access control in healthcare: A survey, issues and challenges, and open issues. J. Netw. Comput. Appl. 2021, 178, 102950. [Google Scholar] [CrossRef]
  24. Hassan, M.U.; Rehmani, M.H.; Chen, J. Privacy preservation in blockchain based IoT systems: Integration issues, prospects, challenges, and future research directions. Future Gener. Comput. Syst. 2019, 97, 512–529. [Google Scholar] [CrossRef]
  25. Greenberger, M. Block what? The unrealized potential of blockchain in healthcare. Nurs. Manag. 2019, 50, 9–12. [Google Scholar] [CrossRef]
  26. Stawicki, S.P.; Firstenberg, M.S.; Papadimos, T.J. What’s new in academic medicine? Blockchain technology in health-care: Bigger, better, fairer, faster, and leaner. Int. J. Acad. Med. 2018, 4, 1. [Google Scholar] [CrossRef]
  27. Rejeb, A.; Bell, L. Potentials of blockchain for healthcare: Case of Tunisia. World Sci. News 2019, 136, 173–193. [Google Scholar] [CrossRef]
  28. Bryatov, S.; Borodinov, A. Blockchain technology in the pharmaceutical supply chain: Researching a business model based on hyperledger fabric. In Proceedings of the International Conference on Information Technology and Nanotechnology (ITNT), Samara, Russia, 21–24 May 2019. [Google Scholar]
  29. Sullivan, C. and E. E-residency and blockchain. Comput. Law Secur. Rev. 2017, 33, 470–481. [Google Scholar] [CrossRef]
  30. Kshetri, N. Blockchain’s roles in strengthening cybersecurity and protecting privacy. Telecommun. Policy 2017, 41, 1027–1038. [Google Scholar] [CrossRef] [Green Version]
  31. Au, M.H.; Yuen, T.H.; Liu, J.K.; Susilo, W.; Huang, X.; Xiang, Y.; Jiang, Z.L. A general framework for secure sharing of personal health records in cloud system. J. Comput. Syst. Sci. 2017, 90, 46–62. [Google Scholar] [CrossRef] [Green Version]
  32. Zhang, Y.; Chen, M.; Leung, V.C.M.; Lai, R. Topical collection on “smart and interactive healthcare systems”. J. Med. Syst. 2017, 41, 1–3. [Google Scholar] [CrossRef] [PubMed]
  33. Liang, X.; Zhao, J.; Shetty, S.; Liu, J.; Li, D. Integrating blockchain for data sharing and collaboration in mobile healthcare applications. In Proceedings of the 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC), Montreal, QC, Canada, 8–13 October 2017; IEEE: Piscataway, NJ, USA, 2017. [Google Scholar]
  34. Zhang, P.; Walker, M.A.; White, J.; Schmidt, D.C.; Lenz, G. Metrics for assessing blockchain-based healthcare decentralized apps. In Proceedings of the 2017 IEEE 19th International Conference on e-Health Networking, Applications and Services (Healthcom), Dalian, China, 12–15 October 2017; IEEE: Piscataway, NJ, USA, 2017. [Google Scholar]
  35. Witchey, N.J. Healthcare Transaction Validation via Blockchain, Systems and Methods. U.S. Patent 10,340,038, 2 July 2019. [Google Scholar]
  36. Alamri, B.; Javed, I.T.; Margaria, T. A GDPR-compliant framework for IoT-based personal health records using blockchain. In Proceedings of the 2021 11th IFIP International Conference on New Technologies, Mobility and Security (NTMS), Paris, France, 19–21 April 2021; IEEE: Piscataway, NJ, USA, 2021. [Google Scholar]
  37. Ichikawa, D.; Kashiyama, M.; Ueno, T. Tamper-resistant mobile health using blockchain technology. JMIR mHealth uHealth 2017, 5, e7938. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Kuo, T.-T.; Kim, H.-E.; Ohno-Machado, L. Blockchain distributed ledger technologies for biomedical and health care applications. J. Am. Med. Inform. Assoc. 2017, 24, 1211–1220. [Google Scholar] [CrossRef] [Green Version]
  39. Randall, D.; Goel, P.; Abujamra, R. Blockchain applications and use cases in health information technology. J. Health Med. Inform. 2017, 8, 8–11. [Google Scholar] [CrossRef]
  40. Vazirani, A.A.; O’Donoghue, O.; Brindley, D.; Meinert, E. Implementing blockchains for efficient health care: Systematic review. J. Med. Internet Res. 2019, 21, e12439. [Google Scholar] [CrossRef] [Green Version]
  41. Khezr, S.; Moniruzzaman, M.; Yassine, A.; Benlamri, R. Blockchain technology in healthcare: A comprehensive review and directions for future research. Appl. Sci. 2019, 9, 1736. [Google Scholar] [CrossRef]
  42. Kshetri, N. Blockchain and electronic healthcare records [cybertrust]. Computer 2018, 51, 59–63. [Google Scholar] [CrossRef]
  43. Brennan, B. Blockchain HIE overview: A framework for healthcare interoperability. Telehealth Med. Today 2017, 2, 1–6. [Google Scholar]
  44. Radanović, I.; Likić, R. Opportunities for use of blockchain technology in medicine. Appl. Health Econ. Health Policy 2018, 16, 583–590. [Google Scholar] [CrossRef] [PubMed]
  45. Dimitrov, D.V. Blockchain applications for healthcare data management. Healthc. Inform. Res. 2019, 25, 51–56. [Google Scholar] [CrossRef]
  46. Kamel Boulos, M.N.; Wilson, J.T.; Clauson, K.A. Geospatial blockchain: Promises, challenges, and scenarios in health and healthcare. Int. J. Heal. Geogr. 2018, 17, 25. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Skiba, D.J. The potential of blockchain in education and health care. Nurs. Educ. Perspect. 2017, 38, 220–221. [Google Scholar] [CrossRef] [PubMed]
  48. Muhammad, G.; Alshehri, F.; Karray, F.; El Saddik, A.; Alsulaiman, M.; Falk, T.H. A comprehensive survey on multimodal medical signals fusion for smart healthcare systems. Inf. Fusion 2021, 76, 355–375. [Google Scholar] [CrossRef]
  49. Nørfeldt, L.; Bøtker, J.; Edinger, M.; Genina, N.; Rantanen, J. Cryptopharmaceuticals: Increasing the safety of medication by a blockchain of pharmaceutical products. J. Pharm. Sci. 2019, 108, 2838–2841. [Google Scholar] [CrossRef] [PubMed]
  50. Park, Y.R.; Lee, E.; Na, W.; Park, S.; Lee, Y.; Lee, J.-H. Is blockchain technology suitable for managing personal health records? Mixed-methods study to test feasibility. J. Med. Internet Res. 2019, 21, e12533. [Google Scholar] [PubMed]
  51. Fan, K.; Wang, S.; Ren, Y.; Li, H.; Yang, Y. Medblock: Efficient and secure medical data sharing via blockchain. J. Med. Syst. 2018, 42, 136. [Google Scholar] [CrossRef]
  52. Vangipuram, S.L.T.; Mohanty, S.P.; Kougianos, E. CoviChain: A blockchain based framework for nonrepudiable contact tracing in healthcare cyber-physical systems during pandemic outbreaks. SN Comput. Sci. 2021, 2, 1–16. [Google Scholar] [CrossRef] [PubMed]
  53. Alsamhi, S.H.; Lee, B.; Guizani, M.; Kumar, N.; Qiao, Y.; Liu, X. Blockchain for decentralized multi-drone to combat COVID-19 and future pandemics: Framework and proposed solutions. Trans. Emerg. Telecommun. Technol. 2021, 32, e4255. [Google Scholar] [CrossRef]
  54. Hassanien, A.E.; Dey, N.; Borra, S. Medical Big Data and Internet of Medical Things: Advances, Challenges and Applications; CRC Press: Boca Raton, FL, USA, 2018. [Google Scholar]
  55. Ahmed, M.; Barkat Ullah, A.S. Infrequent pattern mining in smart healthcare environment using data summarization. J. Supercomput. 2018, 74, 5041–5059. [Google Scholar] [CrossRef]
  56. Dey, N.; Hassanien, A.E.; Bhatt, C.; Ashour, A.; Satapathy, S.C. (Eds.) Internet of Things and Big Data Analytics Toward Next-Generation Intelligence; Springer: Cham, Switzerland, 2018; Volume 35. [Google Scholar]
  57. Kamal, M.; Parvin, S.; Ashour, A.S.; Shi, F.; Dey, N. De-Bruijn graph with MapReduce framework towards metagenomic data classification. Int. J. Inf. Technol. 2017, 9, 59–75. [Google Scholar] [CrossRef]
  58. Mishra, B.S.P.; Das, H.; Dehuri, S.; Jagadev, A.K. (Eds.) Cloud Computing for Optimization: Foundations, Applications, and Challenges; Springer: Cham, Switzerland, 2018. [Google Scholar]
  59. Lianos, I. Blockchain competition. In Ph. Hacker, I. Lianos, G. Dimitropoulos & S. Eich, Regulating Blockchain: Political and Legal Challenges, OUP, 2019; Faculty of Laws, UCL: London, UK, 2018. [Google Scholar]
  60. Sharma, P.; Jindal, R.; Borah, M.D. Blockchain-based integrity protection system for cloud storage. In Proceedings of the 2019 4th Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), Bangkok, Thailand, 11–13 December 2019; IEEE: Piscataway, NJ, USA, 2020. [Google Scholar]
  61. Bano, S.; Al-Bassam, M.; Danezis, G. The road to scalable blockchain designs. USENIX Login Mag. 2017, 42, 31–36. [Google Scholar]
  62. Vukolić, M. The quest for scalable blockchain fabric: Proof-of-work vs. BFT replication. In International Workshop on Open Problems in Network Security; Springer: Cham, Switzerland, 2015. [Google Scholar]
  63. Kokoris-Kogias, E.; Jovanovic, P.; Gasser, L.; Gailly, N.; Syta, E.; Ford, B. Omniledger: A secure, scale-out, decentralized ledger via sharding. In Proceedings of the 2018 IEEE Symposium on Security and Privacy (SP), San Francisco, CA, USA, 20–24 May 2018; IEEE: Piscataway, NJ, USA, 2018. [Google Scholar]
  64. Eyal, I.; Gencer, A.E.; Sirer, E.G.; Van Renesse, R. {Bitcoin-NG}: A scalable blockchain protocol. In Proceedings of the 13th USENIX Symposium on Networked Systems Design and Implementation (NSDI 16), Santa Clara, CA, USA, 16–18 March 2016. [Google Scholar]
  65. Popov, S.; Saa, O.; Finardi, P. Equilibria in the Tangle. Comput. Ind. Eng. 2019, 136, 160–172. [Google Scholar] [CrossRef] [Green Version]
  66. Biswas, S.; Sharif, K.; Li, F.; Nour, B.; Wang, Y. A scalable blockchain framework for secure transactions in IoT. IEEE Internet Things J. 2018, 6, 4650–4659. [Google Scholar] [CrossRef]
  67. Kim, S.; Deka, G.C. (Eds.) Advanced Applications of Blockchain Technology; Springer: Singapore, 2020. [Google Scholar]
  68. Croman, K.; Decker, C.; Eyal, I.; Gencer, A.E.; Juels, A.; Kosba, A.; Miller, A.; Saxena, P.; Shi, E.; Gün Sirer, E.; et al. On scaling decentralized blockchains. In International Conference on Financial Cryptography and Data Security; Springer: Berlin/Heidelberg, Germany, 2016. [Google Scholar]
  69. Nguyen, D.C.; Pathirana, P.N.; Ding, M.; Seneviratne, A. Blockchain for secure ehrs sharing of mobile cloud based e-health systems. IEEE Access 2019, 7, 66792–66806. [Google Scholar] [CrossRef]
  70. Indumathi, J.; Shankar, A.; Ghalib, M.R.; Gitanjali, J.; Hua, Q.; Wen, Z.; Qi, X. Block chain based Internet of Medical Things for uninterrupted, ubiquitous, user-friendly, unflappable, unblemished, unlimited health care services (BC IoMT U 6 HCS). IEEE Access 2020, 8, 216856–216872. [Google Scholar] [CrossRef]
  71. Chamola, V.; Hassija, V.; Gupta, V.; Guizani, M. A comprehensive review of the COVID-19 pandemic and the role of IoT, drones, AI, blockchain, and 5G in managing its impact. IEEE Access 2020, 8, 90225–90265. [Google Scholar] [CrossRef]
  72. Garg, N.; Wazid, M.; Das, A.K.; Singh, D.P.; Rodrigues, J.J.; Park, Y. BAKMP-IoMT: Design of blockchain enabled authenticated key management protocol for internet of medical things deployment. IEEE Access 2020, 8, 95956–95977. [Google Scholar] [CrossRef]
  73. Girardi, F.; De Gennaro, G.; Colizzi, L.; Convertini, N. Improving the healthcare effectiveness: The possible role of EHR, IoMT and blockchain. Electronics 2020, 9, 884. [Google Scholar] [CrossRef]
  74. Sharma, A.; Tomar, R.; Chilamkurti, N.; Kim, B.-G. Blockchain based smart contracts for internet of medical things in e-healthcare. Electronics 2020, 9, 1609. [Google Scholar] [CrossRef]
  75. Meng, W.; Li, W.; Zhu, L. Enhancing medical smartphone networks via blockchain-based trust management against insider attacks. IEEE Trans. Eng. Manag. 2019, 67, 1377–1386. [Google Scholar] [CrossRef]
  76. Mehbodniya, A.; Neware, R.; Vyas, S.; Kumar, M.R.; Ngulube, P.; Ray, S. Blockchain and IPFS integrated framework in bilevel fog-cloud network for security and privacy of IoMT devices. Comput. Math. Methods Med. 2021, 2021, 7727685. [Google Scholar] [CrossRef]
  77. Jolfaei, A.A.; Aghili, S.F.; Singelee, D. A survey on blockchain-based IoMT systems: Towards scalability. IEEE Access 2021, 9, 148948–148975. [Google Scholar] [CrossRef]
  78. Lakhan, A.; Dootio, M.A.; Sodhro, A.H.; Pirbhulal, S.; Groenli, T.M.; Khokhar, M.S.; Wang, L. Cost-efficient service selection and execution and blockchain-enabled serverless network for internet of medical things. Math. Biosci. Eng. 2021, 18, 7344–7362. [Google Scholar] [CrossRef]
  79. Vaiyapuri, T.; Binbusayyis, A.; Varadarajan, V. Security, privacy and trust in IoMT enabled smart healthcare system: A systematic review of current and future trends. Int. J. Adv. Comput. Sci. Appl. 2021, 12, 731–737. [Google Scholar] [CrossRef]
  80. Liang, H.; Wu, J.; Zheng, X.; Zhang, M.; Li, J.; Jolfaei, A. Fog-based secure service discovery for internet of multimedia things: A cross-blockchain approach. ACM Trans. Multimed. Comput. Commun. Appl. (TOMM) 2020, 16, 1–23. [Google Scholar] [CrossRef]
  81. Gul, M.J.; Subramanian, B.; Paul, A.; Kim, J. Blockchain for public health care in smart society. Microprocess. Microsyst. 2021, 80, 103524. [Google Scholar] [CrossRef]
  82. Rachakonda, L.; Bapatla, A.K.; Mohanty, S.P.; Kougianos, E. Sayopillow: Blockchain-integrated privacy-assured iomt framework for stress management considering sleeping habits. IEEE Trans. Consum. Electron. 2020, 67, 20–29. [Google Scholar] [CrossRef]
  83. Jan, M.A.; Cai, J.; Gao, X.-C.; Khan, F.; Mastorakis, S.; Usman, M.; Alazab, M.; Watters, P. Security and blockchain convergence with Internet of Multimedia Things: Current trends, research challenges and future directions. J. Netw. Comput. Appl. 2021, 175, 102918. [Google Scholar] [CrossRef] [PubMed]
  84. Abdel-Basset, M.; Chang, V.; Nabeeh, N.A. An intelligent framework using disruptive technologies for COVID-19 analysis. Technol. Forecast. Soc. Chang. 2021, 163, 120431. [Google Scholar] [CrossRef]
  85. Ersotelos, N.; Bottarelli, M.; Al-Khateeb, H.; Epiphaniou, G.; Alhaboby, Z.; Pillai, P.; Aggoun, A. Blockchain and IoMT against physical abuse: Bullying in schools as a case study. J. Sens. Actuator Netw. 2020, 10, 1. [Google Scholar] [CrossRef]
  86. Elsayeh, M.; Ezzat, K.A.; El-Nashar, H.; Omran, L.N. Cybersecurity architecture for the internet of medical things and connected devices using blockchain. Biomed. Eng. Appl. Basis Commun. 2021, 33, 2150013. [Google Scholar] [CrossRef]
  87. Połap, D.; Srivastava, G.; Yu, K. Agent architecture of an intelligent medical system based on federated learning and blockchain technology. J. Inf. Secur. Appl. 2021, 58, 102748. [Google Scholar] [CrossRef]
  88. Lakhan, A.; Mohammed, M.; Rashid, A.; Kadry, S.; Panityakul, T.; Abdulkareem, K.; Thinnukool, O. Smart-contract aware ethereum and client-fog-cloud healthcare system. Sensors 2021, 21, 4093. [Google Scholar] [CrossRef]
  89. Nguyen, D.C.; Pathirana, P.N.; Ding, M.; Seneviratne, A. BEdgeHealth: A decentralized architecture for edge-based IoMT networks using blockchain. IEEE Internet Things J. 2021, 8, 11743–11757. [Google Scholar] [CrossRef]
  90. Egala, B.S.; Pradhan, A.K.; Badarla, V.; Mohanty, S.P. Fortified-chain: A blockchain-based framework for security and privacy-assured internet of medical things with effective access control. IEEE Internet Things J. 2021, 8, 11717–11731. [Google Scholar] [CrossRef]
  91. Li, X.; Tao, B.; Dai, H.N.; Imran, M.; Wan, D.; Li, D. Is blockchain for Internet of Medical Things a panacea for COVID-19 pandemic? Pervasive Mob. Comput. 2021, 75, 101434. [Google Scholar] [CrossRef]
  92. Kumar, R.; Tripathi, R. Towards design and implementation of security and privacy framework for internet of medical things (iomt) by leveraging blockchain and ipfs technology. J. Supercomput. 2021, 77, 7916–7955. [Google Scholar] [CrossRef]
  93. Ren, Y.; Zhu, F.; Zhu, K.; Sharma, P.K.; Wang, J. Blockchain-based trust establishment mechanism in the internet of multimedia things. Multimed. Tools Appl. 2021, 80, 30653–30676. [Google Scholar] [CrossRef]
  94. Allouche, M.; Mitrea, M.; Moreaux, A.; Kim, S.-K. Automatic smart contract generation for internet of media things. ICT Express 2021, 7, 274–277. [Google Scholar] [CrossRef]
  95. Majeed, A.; Lee, S. Applications of machine learning and high-performance computing in the era of COVID-19. Appl. Syst. Innov. 2021, 4, 40. [Google Scholar] [CrossRef]
  96. Mantey, E.A.; Zhou, C.; Anajemba, J.H.; Okpalaoguchi, I.M.; Chiadika, O.D.-M. Blockchain-secured recommender system for special need patients using deep learning. Front. Public Health 2021, 9, 737269. [Google Scholar] [CrossRef] [PubMed]
  97. Alotaibi, A.S. Biserial Miyaguchi–Preneel blockchain-based Ruzicka-indexed deep perceptive learning for malware detection in IoMT. Sensors 2021, 21, 7119. [Google Scholar] [CrossRef]
  98. Jin, H.; Dai, X.; Xiao, J.; Li, B.; Li, H.; Zhang, Y. Cross-cluster federated learning and blockchain for internet of medical things. IEEE Internet Things J. 2021, 8, 15776–15784. [Google Scholar] [CrossRef]
  99. Gao, Y.; Lin, H.; Chen, Y.; Liu, Y. Blockchain and SGX-enabled edge-computing-empowered secure IoMT data analysis. IEEE Internet Things J. 2021, 8, 15785–15795. [Google Scholar] [CrossRef]
  100. Abdellatif, A.A.; Samara, L.; Mohamed, A.; Erbad, A.; Chiasserini, C.F.; Guizani, M.; O’Connor, M.D.; Laughton, J. Medge-chain: Leveraging edge computing and blockchain for efficient medical data exchange. IEEE Internet Things J. 2021, 8, 15762–15775. [Google Scholar] [CrossRef]
  101. Lin, P.; Song, Q.; Yu, F.R.; Wang, D.; Guo, L. Task offloading for wireless VR-enabled medical treatment with blockchain security using collective reinforcement learning. IEEE Internet Things J. 2021, 8, 15749–15761. [Google Scholar] [CrossRef]
  102. Zaabar, B.; Cheikhrouhou, O.; Jamil, F.; Ammi, M.; Abid, M. HealthBlock: A secure blockchain-based healthcare data management system. Comput. Netw. 2021, 200, 108500. [Google Scholar] [CrossRef]
  103. Rahman, M.Z.U.; Surekha, S.; Satamraju, K.P.; Mirza, S.S.; Lay-Ekuakille, A. A collateral sensor data sharing framework for decentralized healthcare systems. IEEE Sens. J. 2021, 21, 27848–27857. [Google Scholar] [CrossRef]
  104. Saidi, H.; Labraoui, N.; Ari, A.A.A.; Maglaras, L.A.; Emati, J.H.M. DSMAC: Privacy-aware decentralized self-management of data access control based on blockchain for health data. IEEE Access 2022, 10, 101011–101028. [Google Scholar] [CrossRef]
  105. Zhao, Y.; Hu, N.; Zhao, Y.; Zhang, Y. A trusted and privacy-preserved dispersed computing scheme for the Internet of Mobile Things. Secur. Commun. Netw. 2022, 2022, 8034677. [Google Scholar] [CrossRef]
  106. Khan, A.A.; Wagan, A.A.; Laghari, A.A.; Gilal, A.R.; Aziz, I.A.; Talpur, B.A. BIoMT: A state-of-the-art consortium serverless network architecture for healthcare system using blockchain smart contracts. IEEE Access 2022, 10, 78887–78898. [Google Scholar] [CrossRef]
  107. Srivastava, J.; Routray, S.; Ahmad, S.; Waris, M.M. Internet of Medical Things (IoMT)-based smart healthcare system: Trends and progress. Comput. Intell. Neurosci. 2022, 2022, 7218113. [Google Scholar] [CrossRef] [PubMed]
  108. Rajadevi, R.; Venkatachalam, K.; Masud, M.; AlZain, M.A.; Abouhawwash, M. Proof of activity protocol for IoMT data security. Comput. Syst. Sci. Eng. 2023, 44, 339–350. [Google Scholar] [CrossRef]
  109. Punithavathi, R.; Venkatachalam, K.; Masud, M.; AlZain, M.A.; Abouhawwash, M. Crypto hash based malware detection in IoMT framework. Intell. Autom. Soft Comput. 2022, 34, 559–574. [Google Scholar] [CrossRef]
  110. Delgado, R.M. Without IPv6, there is no digital transformation for healthcare. Technol. Health Care 2022, 30, 505–508. [Google Scholar] [CrossRef]
  111. Nie, X.; Zhang, A.; Chen, J.; Qu, Y.; Yu, S. Blockchain-empowered secure and privacy-preserving health data sharing in edge-based IoMT. Secur. Commun. Netw. 2022, 2022, 8293716. [Google Scholar] [CrossRef]
  112. Liu, Y.; Shan, G.; Liu, Y.; Alghamdi, A.; Alam, I.; Biswas, S. Blockchain bridges critical national infrastructures: E-healthcare data migration perspective. IEEE Access 2022, 10, 28509–28519. [Google Scholar] [CrossRef]
  113. Hilal, A.M.; Hassine, S.B.H.; Larabi-Marie-Sainte, S.; Nemri, N.; Nour, M.K.; Motwakel, A.; Zamani, A.S.; Al Duhayyim, M. Malware detection using decision tree based SVM classifier for IoT. Comput. Mater. Contin. 2022, 72, 713–726. [Google Scholar]
  114. Ravikumar, G.; Venkatachalam, K.; Masud, M.; Abouhawwash, M. Cost efficient scheduling using smart contract cognizant ethereum for IoMT. Intell. Autom. Soft Comput. 2022, 33, 865–877. [Google Scholar] [CrossRef]
  115. Ali, A.; Almaiah, M.A.; Hajjej, F.; Pasha, M.F.; Fang, O.H.; Khan, R.; Teo, J.; Zakarya, M. An industrial IoT-based blockchain-enabled secure searchable encryption approach for healthcare systems using neural network. Sensors 2022, 22, 572. [Google Scholar] [CrossRef]
  116. Duhayyim, M.A.; Al-Wesabi, F.N.; Marzouk, R.; Musa, A.I.A.; Negm, N.; Hilal, A.M.; Hamza, M.A.; Rizwanullah, M. Integration of fog computing for health record management using blockchain technology. Comput. Mater. Contin. 2022, 71, 4135–4149. [Google Scholar] [CrossRef]
  117. Almaiah, M.A.; Hajjej, F.; Ali, A.; Pasha, M.F.; Almomani, O. An AI enabled hybrid lightweight authentication model for digital healthcare using industrial Internet of Things cyber physical systems. Sensors 2022, 22, 1448. [Google Scholar] [CrossRef] [PubMed]
  118. Pelekoudas-Oikonomou, F.; Zachos, G.; Papaioannou, M.; de Ree, M.; Ribeiro, J.C.; Mantas, G.; Rodriguez, J. Blockchain-based security mechanisms for IoMT Edge networks in IoMT-based healthcare monitoring systems. Sensors 2022, 22, 2449. [Google Scholar] [CrossRef] [PubMed]
  119. Rachakonda, L.; Bapatla, A.K.; Mohanty, S.P.; Kougianos, E. BACTmobile: A smart blood alcohol concentration tracking mechanism for smart vehicles in healthcare CPS framework. SN Comput. Sci. 2022, 3, 1–24. [Google Scholar] [CrossRef]
  120. Xiong, H.; Jin, C.; Alazab, M.; Yeh, K.-H.; Wang, H.; Gadekallu, T.R.; Wang, W.; Su, C. On the design of blockchain-based ECDSA with fault-tolerant batch verification protocol for blockchain-enabled IoMT. IEEE J. Biomed. Health Inform. 2021, 26, 1977–1986. [Google Scholar] [CrossRef]
  121. Wu, G.; Wang, S.; Ning, Z.; Records, J.L. Blockchain-enabled privacy-preserving access control for data publishing and sharing in the Internet of Medical Things. IEEE Internet Things J. 2021, 9, 8091–8104. [Google Scholar] [CrossRef]
  122. Wang, W.; Chen, Q.; Yin, Z.; Srivastava, G.; Gadekallu, T.R.; Alsolami, F.; Su, C. Blockchain and PUF-based lightweight authentication protocol for wireless medical sensor networks. IEEE Internet Things J. 2021, 9, 8883–8891. [Google Scholar] [CrossRef]
  123. Nasir, M.U.; Khan, S.; Mehmood, S.; Khan, M.A.; Rahman, A.U.; Hwang, S.O. IoMT-based osteosarcoma cancer detection in histopathology images using transfer learning empowered with blockchain, fog computing, and edge computing. Sensors 2022, 22, 5444. [Google Scholar] [CrossRef] [PubMed]
  124. Bai, P.; Kumar, S.; Aggarwal, G.; Mahmud, M.; Kaiwartya, O.; Lloret, J. Self-sovereignty identity management model for smart healthcare system. Sensors 2022, 22, 4714. [Google Scholar] [CrossRef] [PubMed]
  125. Al-Otaibi, Y.D. K-nearest neighbour-based smart contract for internet of medical things security using blockchain. Comput. Electr. Eng. 2022, 101, 108129. [Google Scholar] [CrossRef]
  126. Lakhan, A.; Mohammed, M.A.; Elhoseny, M.; Alshehri, M.D.; Abdulkareem, K.H. Blockchain multi-objective optimization approach-enabled secure and cost-efficient scheduling for the Internet of Medical Things (IoMT) in fog-cloud system. Soft Comput. 2022, 26, 6429–6442. [Google Scholar] [CrossRef]
  127. Annane, B.; Alti, A.; Lakehal, A. Blockchain based context-aware CP-ABE schema for Internet of Medical Things security. Array 2022, 14, 100150. [Google Scholar] [CrossRef]
  128. Wang, Y.; Zhang, A.; Zhang, P.; Qu, Y.; Yu, S. Security-aware and privacy-preserving personal health record sharing using consortium blockchain. IEEE Internet Things J. 2021, 9, 12014–12028. [Google Scholar] [CrossRef]
  129. Bhattacharjya, A.; Kozdrój, K.; Bazydło, G.; Wisniewski, R. Trusted and secure blockchain-based architecture for Internet-of-Medical-Things. Electronics 2022, 11, 2560. [Google Scholar] [CrossRef]
  130. Ktari, J.; Frikha, T.; Ben Amor, N.; Louraidh, L.; Elmannai, H.; Hamdi, M. IoMT-based platform for E-health monitoring based on the blockchain. Electronics 2022, 11, 2314. [Google Scholar] [CrossRef]
  131. Rahman, M.S.; Alabdulatif, A.; Khalil, I. Privacy aware internet of medical things data certification framework on healthcare blockchain of 5G Edge. Comput. Commun. 2022, 192, 373–381. [Google Scholar] [CrossRef]
  132. Debauche, O.; Penka, J.B.N.; Mahmoudi, S.; Lessage, X.; Hani, M.; Manneback, P.; Lufuluabu, U.K.; Bert, N.; Messaoudi, D.; Guttadauria, A. RAMi: A new real-time Internet of Medical Things architecture for elderly patient monitoring. Information 2022, 13, 423. [Google Scholar] [CrossRef]
  133. Salonikias, S.; Khair, M.; Mastoras, T.; Mavridis, I. Blockchain-based access control in a globalized healthcare provisioning ecosystem. Electronics 2022, 11, 2652. [Google Scholar] [CrossRef]
  134. Bathalapalli, V.K.; Mohanty, S.P.; Kougianos, E.; Baniya, B.K.; Rout, B. PUFchain 2.0: Hardware-assisted robust blockchain for sustainable simultaneous device and data security in smart healthcare. SN Comput. Sci. 2022, 3, 344. [Google Scholar] [CrossRef] [PubMed]
  135. Nasir, M.U.; Zubair, M.; Ghazal, T.M.; Khan, M.F.; Ahmad, M.; Rahman, A.-U.; Al Hamadi, H.; Khan, M.A.; Mansoor, W. Kidney cancer prediction empowered with blockchain security using transfer learning. Sensors 2022, 22, 7483. [Google Scholar] [CrossRef] [PubMed]
  136. Yu, S.; Park, Y. A robust authentication protocol for wireless medical sensor networks using blockchain and physically unclonable functions. IEEE Internet Things J. 2022, 9, 20214–20228. [Google Scholar] [CrossRef]
  137. Rehman, A.; Abbas, S.; Khan, M.; Ghazal, T.M.; Adnan, K.M.; Mosavi, A. A secure healthcare 5.0 system based on blockchain technology entangled with federated learning technique. Comput. Biol. Med. 2022, 150, 106019. [Google Scholar] [CrossRef]
  138. Kumar, M.; Verma, S.; Kumar, A.; Ijaz, M.F.; Rawat, D.B. ANAF-IoMT: A novel architectural framework for IoMT-enabled smart healthcare system by enhancing security based on RECC-VC. IEEE Trans. Ind. Inform. 2022, 18, 8936–8943. [Google Scholar] [CrossRef]
  139. Ming, Z.; Zhou, M.; Cui, L.; Yang, S. FAITH: A fast blockchain-assisted edge computing platform for healthcare applications. IEEE Trans. Ind. Inform. 2022, 18, 9217–9226. [Google Scholar] [CrossRef]
  140. McGhin, T.; Choo, K.-K.R.; Liu, C.Z.; He, D. Blockchain in healthcare applications: Research challenges and opportunities. J. Netw. Comput. Appl. 2019, 135, 62–75. [Google Scholar] [CrossRef]
  141. Qayyum, A.; Qadir, J.; Bilal, M.; Al-Fuqaha, A. Secure and robust machine learning for healthcare: A survey. IEEE Rev. Biomed. Eng. 2020, 14, 156–180. [Google Scholar] [CrossRef]
Figure 1. The number of publications produced by the subject area between 2017 and 2022.
Figure 1. The number of publications produced by the subject area between 2017 and 2022.
Applsci 13 01287 g001
Figure 2. The number of publications published annually between 2017 and 2022.
Figure 2. The number of publications published annually between 2017 and 2022.
Applsci 13 01287 g002
Figure 3. Main keywords of articles.
Figure 3. Main keywords of articles.
Applsci 13 01287 g003
Figure 4. Conceptual design for the IoMT.
Figure 4. Conceptual design for the IoMT.
Applsci 13 01287 g004
Table 1. Count of publications in various journals.
Table 1. Count of publications in various journals.
JournalNumber of Publications
IEEE Internet of Things Journal10
IEEE Access8
Sensors8
Electronics Switzerland5
SN Computer Science3
Computers Materials and Continua2
IEEE Transactions on Industrial Informatics2
Intelligent Automation and Soft Computing2
International Journal of Advanced Computer Science and Applications2
Security and Communication Networks2
ACM Transactions on Multimedia Computing Communications and Applications1
Applied System Innovation1
Array1
Biomedical Engineering Applications Basis and Communications1
Computational and Mathematical Methods in Medicine1
Computational Intelligence and Neuroscience1
Computer Communications1
Computer Networks1
Computer Systems Science and Engineering1
Computers and Electrical Engineering1
Computers in Biology and Medicine1
Frontiers in Public Health1
ICT Express1
IEEE Journal of Biomedical and Health Informatics1
IEEE Sensors Journal1
IEEE Transactions on Consumer Electronics1
IEEE Transactions on Engineering Management1
Information Switzerland1
Journal of Information Security and Applications1
Journal of Network and Computer Applications1
Journal of Sensor and Actuator Networks1
Journal of Supercomputing1
Mathematical Biosciences and Engineering1
Microprocessors And Microsystems1
Multimedia Tools and Applications1
Pervasive and Mobile Computing1
Soft Computing1
Technological Forecasting and Social Change1
Technology and Health Care1
Table 2. Studies on blockchain’s potential use in IoMT systems (2017–2022).
Table 2. Studies on blockchain’s potential use in IoMT systems (2017–2022).
ObjectiveYearJournalCited byReference
“Blockchain For Secure EHR Cloud-Based Mobile E-Health System Sharing”2019IEEE Access280[69]
“Protecting The Internet of Medical Devices with Blockchain”2019International Journal of Advanced Computer Science and Applications51[20]
“Blockchain-Based IoMT for Uninterrupted, Ubiquitous, User-Friendly, Unfaltering, Flawless, Unrestricted Health Care Services (BC IoMT U6HCS)”2020IEEE Access29[70]
“An In-Depth Analysis of the COVID-19 Pandemic and the Role of IoT, Drones, AI, Blockchain, and 5G in Managing its Effects”2020IEEE Access818[71]
“Design of Blockchain-Enabled Authenticated Key Management Protocol for Deployment of Internet of Medical Devices”2020IEEE Access77[72]
“The Prospective Use of EHR, IoMT, and Blockchain in Improving Healthcare Effectiveness”2020Electronics (Switzerland)30[73]
“E-healthcare Blockchain-Based Smart Contracts for The Internet of Medical Devices”2020Electronics (Switzerland)75[74]
“Enhancing Medical Smartphone Networks Against Insider Attacks Using Blockchain-Based Trust Management”2020IEEE Transactions on Engineering Management65[75]
“Integrated Blockchain and IPFS Framework in Bilevel Fog-Cloud Network for IoMT Device Security and Privacy”2021Computational and Mathematical Methods in Medicine5[76]
“Scalability of Blockchain-Based IoMT Systems”2021IEEE Access6[77]
“Blockchain-enabled serverless network with cost-effective service selection and execution for the IoMT”2021Mathematical Biosciences and Engineering18[78]
“A Systematic Analysis of Current and Future Trends in IoMT-Enabled Smart Healthcare Systems’ Security, Privacy, and Trust”2021International Journal of Advanced Computer Science and Applications18[79]
“A Cross-blockchain Approach to Fog-based Secure Service Discovery for Internet of Multimedia Things”2021ACM Transactions on Multimedia Computing, Communications, and Applications6[80]
“Blockchain for Public Healthcare in The Intelligent Society”2021Microprocessors and Microsystems24[81]
“SaYoPillow: A Blockchain-Integrated, Privacy-Assured IoMT Framework for Stress Management Taking Sleeping Habits into Consideration”2021IEEE Transactions on Consumer Electronics26[82]
“Convergence of security and Blockchain with the Internet of Multimedia Things: Current trends, research problems, and future directions”2021Journal of Network and Computer Applications40[83]
“Intelligent Framework Using Disruptive Technologies for Analysis of COVID-19”2021Technological Forecasting and Social Change167[84]
“A Case Study Using Blockchain and IoMT against Physical Abuse: School Bullying”2021Journal of Sensor and Actuator Networks5[85]
“Blockchain-Based Cybersecurity Architecture for the IoMT and Linked Devices”2021Biomedical Engineering—Applications, Basis, and Communications4[86]
“Intelligent Medical System Agent Architecture Based on Federated Learning and Blockchain Technologies”2021Journal of Information Security and Applications47[87]
“Smart-Contract-Aware Ethereum and Client-Cloud Fog-Computing Healthcare System”2021Sensors51[88]
“BEdgeHealth: A Blockchain-based decentralized architecture for edge-based IoMT networks”2021IEEE Internet of Things Journal40[89]
“Fortified-Chain: A Blockchain-Based Framework with Effective Access Control for Securing and Protecting the IoMT”2021IEEE Internet of Things Journal68[90]
“Blockchain Technology for the IoMT, A Remedy for COVID-19”2021Pervasive and Mobile Computing20[91]
“Utilizing Blockchain and IPFS Technologies to Build and Deploy a Security and Privacy Framework for IoMT”2021Journal of Supercomputing36[92]
“The Mechanism for Establishing Trust in the Internet of Multimedia Things Based on Blockchain Technology”2021Multimedia Tools and Applications11[93]
“Automatic Creation of Smart Contracts for the Internet of Media Things”2021ICT Express4[94]
“A Blockchain-Based Framework for Non-repudiable Contact Tracing in Healthcare Cyber-physical Systems During Pandemic Outbreaks”2021SN Computer Science17[52]
“In the Age of COVID-19, Applications of Machine Learning and High-Performance Computing”2021Applied System Innovation6[95]
“Deep Learning-Based Blockchain-Secured Recommendation System for Patients with Special Needs”2021Frontiers in Public Health4[96]
“Blockchain-Based Miyauchi–preneel ruzickaindexed Deep Perceptive Learning for Malware Detection in IoMT”2021Sensors3[97]
“Federated Learning Across Clusters and Blockchain for the IoMT”2021IEEE Internet of Things Journal13[98]
“Secure IoMT Data Analysis Powered by Blockchain and SGX-Enabled Edge Computing”2021IEEE Internet of Things Journal15[99]
“MEdge-Chain: Using Edge Computing and Blockchain to Exchange Medical Data Efficiently”2021IEEE Internet of Things Journal53[100]
“Applying Collective Reinforcement Learning to Task Offloading for VR-Enabled Wireless Medical Treatment with Blockchain Security”2021IEEE Internet of Things Journal27[101]
“HealthBlock is a Secure Blockchain-Based Solution for Managing Healthcare Data”2021Computer Networks31[102]
“A Framework for Sharing Collateral Sensor Data in Decentralized Healthcare Systems”2021IEEE Sensors Journal2[103]
“DSMAC: Privacy-Aware Blockchain-Based Decentralized Self-Management of Health Data Access Control”2022IEEE Access0[104]
“Trusted and Confidentiality-Preserving Distributed Computing for the Internet of Mobile Things”2022Security and Communication Networks0[105]
“BIoMT: A State-of-the-Art Serverless Network Architecture for a Blockchain-Based Healthcare System”2022IEEE Access2[106]
“Trends and Progress of Smart Healthcare System Based on the IoMT”2022Computational Intelligence and Neuroscience1[107]
“Protocol for Proof of Activity for IoMT Data Security”2022Computer Systems Science and Engineering0[108]
“IoMT Framework Crypto Hash-Based Malware Detection”2022Intelligent Automation and Soft Computing2[109]
“Without IPv6, Healthcare Digital Transformation is Impossible”2022Technology and Health Care0[110]
“Blockchain-Enabled Secure and Privacy-Preserving Sharing of Health Data at the Edge of IoMT”2022Security and Communication Networks2[111]
“Blockchain Connects Critical National Infrastructures: A Perspective on E-Healthcare Data Migration”2022IEEE Access2[112]
“IoT Malware Detection Employing a Decision Tree-Based SVM Classifier”2022Computers, Materials and Continua0[113]
“Cost-Effective Scheduling Using Ethereum Smart Contracts for IoMT”2022Intelligent Automation and Soft Computing0[114]
“Neural Network-Based Industrial IoT-Based Blockchain-Enabled Secure Searchable Encryption for Healthcare Systems”2022Sensors18[115]
“Integration of Blockchain Technology with Fog Computing for the Administration of Medical Records”2022Computers, Materials and Continua3[116]
“An Artificial IntelligenceEnabled Hybrid Lightweight Authentication Model for Digital Healthcare Utilizing Industrial IoT CyberPhysical Systems”2022Sensors0[117]
“Blockchain-Based IoMT Edge Network Security Mechanisms in IoMT-Based Healthcare Monitoring Systems”2022Sensors7[118]
“BACTmobile: An Intelligent Blood Alcohol Concentration Monitoring System for Smart Vehicles in the Healthcare CPS Framework”2022SN Computer Science1[119]
Regarding the Design of “Blockchain-Based ECDSA With a Fault-Tolerant Batch Verification Protocol for Blockchain-Enabled IoMT”2022IEEE Journal of Biomedical and Health Informatics52[120]
“Blockchain-Enabled Access Control that Preserves Privacy for Data Publication and Sharing in the IoMT”2022IEEE Internet of Things Journal6[121]
“Lightweight Authentication Protocol for Wireless Medical Sensor Networks Based on Blockchain and PUF”2022IEEE Internet of Things Journal65[122]
“IoMT-Based Osteosarcoma Cancer Detection in Histopathology Images using Transfer Learning, Blockchain, Fog Computing, and Edge Computing”2022Sensors1[123]
“Smart Healthcare System Management Model for Self-Sovereignty Identities”2022Sensors1[124]
“K-Nearest Neighbor-Based Smart Contract for the Security of the Internet of Medical Devices Utilizing Blockchain”2022Computers and Electrical Engineering0[125]
“Blockchain Multi-objective Optimization Enables Cost-effective and Secure Scheduling for the IoMT in a Fog-cloud Environment”2022Soft Computing8[126]
“Context-aware blockchain-based CP-ABE schema for IoMT security”2022Array1[127]
“Sharing of Secure and Confidential Personal Health Records Using Consortium Blockchain”2022IEEE Internet of Things Journal2[128]
“Trusted and Secure Blockchain-Based IoMT Architecture”2022Electronics1[129]
“Blockchain-Based IoMT-Based Platform for E-Health Monitoring”2022Electronics4[130]
“Privacy-Aware IoMT Data Certification Framework on the Healthcare Blockchain”2022Computer Communications0[131]
“RAMi: A New Real-Time IoMT Architecture for Monitoring of Elderly Patients”2022Information0[132]
“Access Control Based on Blockchain Technology in a Globalized Healthcare Provisioning Ecosystem”2022Electronics0[133]
“PUFchain 2.0: Hardware-Assisted Robust Blockchain for Sustainably Concurrent Device and Data Security in Smart Healthcare”2022SN Computer Science0[134]
“Prediction of Kidney Cancer Facilitated by Blockchain Security and Transfer Learning”2022Sensors0[135]
“A Secure Authentication Protocol for Wireless Medical Sensor Networks Based on Blockchain and Physically Unclonable Functions”2022IEEE Internet of Things Journal9[136]
“A Secure Healthcare 5.0 System Using Blockchain Technology and Federated Learning”2022Computers in Biology and Medicine0[137]
“ANAF-IoMT: An Innovative Architectural Framework for IoMT-Enabled Smart Healthcare Systems by Strengthening Security Using RECC-VC”2022IEEE Transactions on Industrial Informatics3[138]
“FAITH: A Rapid Edge Computing Platform with Blockchain Support for Healthcare Applications”2022IEEE Transactions on Industrial Informatics1[139]
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Taherdoost, H. Blockchain-Based Internet of Medical Things. Appl. Sci. 2023, 13, 1287. https://doi.org/10.3390/app13031287

AMA Style

Taherdoost H. Blockchain-Based Internet of Medical Things. Applied Sciences. 2023; 13(3):1287. https://doi.org/10.3390/app13031287

Chicago/Turabian Style

Taherdoost, Hamed. 2023. "Blockchain-Based Internet of Medical Things" Applied Sciences 13, no. 3: 1287. https://doi.org/10.3390/app13031287

APA Style

Taherdoost, H. (2023). Blockchain-Based Internet of Medical Things. Applied Sciences, 13(3), 1287. https://doi.org/10.3390/app13031287

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop