T.S.Raja Rajeswari, Sk. Khaja Shareef, Sameer Khan, N Venkatesh · 6 authors
Every year a lot of students graduate from the universities due to which a huge number of certificates are generated. The problem arises when it comes to authenticate these certificates. At present there is no such mechanism to validate the certificates. Hence, a lot of certificates are forged every year and are being used to fulfill their job requirements. To overcome this problem a decentralized web application is built that registers the certificate on ethereum blockchain and a smart contract to validate the certificates on blockchain. Once the data is entered by the user the details of certificates are pushed on ethereum blockchain using hashing. Using this generated hash we can verify the authenticity of the user.
Blockchain has emerged as a key technology for ensuring reliability and security in several application areas primarily including the healthcare sector. Blockchain is a distributed ledger where blocks of transactions are connected in a chain using the cryptographic hash function of the previous block, making it an append-only structure. Any modification on any of the blocks will generate different hash values in other blocks in a cascading manner and different link relations. In this way the blockchain achieves immutability and security. Blockchain also involves consensus mechanisms in order to ensure synchronization among blocks and agreement between existing nodes to add a new transaction in the chain. Healthcare data is highly sensitive in nature, which consists of private information related to the diagnosis and treatment of patients. In traditional approach these data are stored by each hospital separately where sharing data is very time consuming. Also, health data is very limited to access due to the risk of disclosure of sensitive information. In order to address these issues, the objective of this paper is to integrate blockchain technology with healthcare records/data in order to provide better sharing of data without the fear of data tampering or security breach.
Ophthalmology has been an early adopter of cutting-edge digital technology such as artificial intelligence (AI) and could be primed to integrate blockchain architecture in the management of AI and big data analytics. Blockchain technology has seen rapid development and maturation over the past few years. Invented in 2008 by Satoshi Nakamoto (a presumed pseudonym for an anonymous inventor/group of inventors), the blockchain ledger, forming the basis of Bitcoin, was the first decentralized cryptocurrency.1 Since then, different blockchain infrastructures, with different consensus frameworks have emerged, such as Ethereum2 and Hyperledger Fabric.3 In essence, blockchain is a decentralized ledger with immutable properties allowing secure verifiable transfer of data in a peer-to-peer fashion, utilizing a common consensus protocol to prevent single points of failure. A variety of use cases have been developed to harness the advantages of blockchain technology, largely in the financial sector and the business world. However, the health care sector, which requires tight control over confidential medical data, is well-poised to take advantage of the unique characteristics of blockchain technology. This could be of particular relevance in the management of big data and AI research, notably in the field of ophthalmology which has an abundance of numerical data and imagery. In this review, we introduce the basic concepts of blockchain technology, discuss its unique advantages and its use case in ophthalmology. BLOCKCHAIN TECHNOLOGY The concept of blockchain technology is built on a framework of an ever-growing list (or “chain”) of transactions, grouped into units called “blocks”, which in turn are linked to their immediate predecessors by a unique cryptographic “hash value”. Generated from specific mathematical algorithms such as the SHA-256 (256-bit Secure Hash Algorithm), hash values are characterized by their deterministic value, as well as pre-image and collision resistance, serving as “fingerprint” of a block and its content. Blockchain platforms depend on “consensus protocols” to approve, record, and validate each transaction. A consensus protocol is a form of rules to reach a common majority agreement on the present state of the ledger within a blockchain network. Once a consensus has been reached, the block containing the log of the data is added into the “chain”, and shared with every stakeholder in the network, known individually as “nodes”. The archetypal example would be a bitcoin transaction. When the transfer of coins is initiated between 2 parties, miners compete for the right to record the transaction by solving a difficult mathematical puzzle, expanding precious energy in the process. The node that solves the puzzle first is recognized for its efforts and given the right to record the transaction, hence reaching a consensus. The common transparency and traceability of each individual cryptoasset transaction prevent duplicative transactions, solving the well-documented “double-spend” problem—an inherent flaw in digital asset schemes where the same single-use digital token is spent more than once. This forms the basis of a hack-resistant, immutable distributed ledger. Current blockchain platforms can be broadly dichotomized into two main groups—permissionless or permitted (Fig. 1). Permissionless blockchain platforms such as Bitcoin and Ethereum provide unrestricted access to the public. Conversely, permitted platforms such as Hyperledger Fabric will retain a central approving authority. Hybrid or consortium-based blockchain platforms are derived from a combination of these two architectures, resulting in partial centralization with participation restricted through the private network. Table 1 provides a summary of the terms and definitions unique to blockchain technology.FIGURE 1: Permissionless blockchain targets at implementing a common platform that can involve anyone with anonymous identity into the network, which often comes with built-in currency and is public, open and fully decentralized; Permitted blockchain engages a few organizations with known identity (forming a consortium) that require collaborative operations to realize specific business logics, which are co-hosted/co-managed by the consortium. TABLE 1 - Summary of Common Terms and Definitions in Blockchain Technology Ledger Book or computer file for recording and totaling transactions Blocks Transactions cumulated and recorded into fixed sized blocks. Each block contains timestamp, a unique hash, the hash of the previous block and transaction data 23 Chain List of blocks linked cryptographically23 Hash Cryptographically generated fixed length string of values, based on random input of transactions/data, that is easily verifiable23 Mining Validating of transactions and recording onto the decentralized ledger24 Byzantine generals problem Computer science description of a situation where involved parties must reach a decision to avoid failure, but some parties are dishonest or malicious25,26 Consensus protocol A form of rules to reach a common majority agreement on the present state of the ledger within a blockchain network23 Fault tolerance Level that allows a system to continue operating normally in the event of failure of some components or nodes27 Nodes Communicating points that may perform different functions on the blockchain platform23 Permissioned Access control layer governed by a central authority23 Permissionless Public access without restriction to participation23 Hybrid/Consortium Blockchain platform governed by multiple organizations23 Immutable Unchangeable ledger23,24 Cryptoasset Digital assets that utilizes cryptography as a medium for transactions24 Smart contracts Automated executions of complex transactions based on computational logic when certain conditions are met24 Asymptotic security Security if and only if the adversary's advantage is a negligible function of the security parameters i.e. a secure scheme that is conditionally proven to be harder than any polynomial for the attacker to break28 Deterministic Same operation performed by different nodes will produce the same result29 Pre-image resistance Computationally infeasible to derive the original transaction data from a given hash function30 Collision resistance Computationally infeasible for two distinct inputs to result in the same hash output23 APPLICATIONS OF BLOCKCHAIN TECHNOLOGY Apart from application in finance, blockchain technology could be highly relevant in other industries such as health care, insurance, and supply chain management4 due to the inherent key advantages: immutable transaction records, decentralized peer-to-peer transaction, costless verification, reduction of incumbent market power, avoidance of single point of failure, and smart contracts – automated executions of complex transactions based on computational logic. Although it has yet to achieve mass-market adoption, blockchain technology has been heavily touted as a potential general-purpose technology, gaining traction across multiple industries such as finance, hedge fund management, and supply chain management.4 Years of reliance on antiquated digital systems have resulted in cumbersome, inefficient and resource-intensive processes. This results in significant resource wastage, and also renders systems susceptible to fraudulent attacks or system-wide failure.5 Financial institutions are therefore innovating with blockchain technology to address these concerns. Another frontrunner in the adoption of blockchain technology is supply chain management.6–8 The complex multi-faceted nature of supply chains places heavy demands on proper record keeping, quality control, and transaction monitoring. Current supply chains rely on centralized intermediation entities with little transparency across the entire chain. The supply chain thus suffers from vulnerability towards malicious modification or human errors and poor accountability. The application of blockchain technologies has the potential to disrupt the industry by effectively eliminating the trust required between involved parties. By transferring the onus of trust onto the algorithm and its immutable record, the issues associated with the need of verifying intermediaries can be eliminated.9 BLOCKCHAIN TECHNOLOGY IN HEALTH CARE In a 2019 technical report by International Telecommunication Union,10 the Telecommunication Standardization Sector identified the health care sector as one of the key sectors that could be a beneficiary of blockchain technology. The devastating COVID-19 pandemic, while unfortunate, has provided a significant impetus to accelerate this process.11 It is important to note that traditional distributed database management system (DDMS) can support the secure transfer of health data through encryption and data masking with the acceptance of several significant flaws: potential single point of failure, subject identification and tampering of data. In comparison, blockchain armed with asymmetric encryption and hash values can surmount these challenges albeit with a measured sacrifice of throughput rate and latency. At this point, adoption of blockchain in health care is still in its infancy with multiple proof of concepts but a limited selection of commercially available health care blockchain platforms. At present, most of these platforms are focused on electronic medical record management, such as patient-controlled electronic medical record (EMR) accessibility and immutable recording of clinical records. One of the most well-known is Medicalchain (Medicalchain SA, London) which is built on the Hyperledger Fabric architecture. Medicalchain's12 primary focus is to assign EMR access-granting rights to the patient, thereby returning control back to the patient. It provides a self-contained incentive system by rewarding data-sharing behavior with its native token (MedToken) which can be utilized in exchange for relevant services. Another example is the national rollout of the e-Estonia health care EMR built on Keyless Signature Infrastructure blockchain technology, allowing for verification of integrity of accessed medical records as well as immutable record of access logs.13 Since its inception in 2016, it has enabled digital permeation with 99% of health data digitized securely and handling up to 1.8 million patient queries every month, made possible through decentralized authenticated sharing of data. Notable examples of data sharing on the e-Estonia platform include physician retrieval of time-critical patient information during emergencies as well as patient monitored access of their medical data.14 Separately, blockchain could potentially be a disrupting technology in the health care supply chain and insurance field. The decentralized nature of blockchain provides a platform for cross-institution and cross-border collaboration, providing transparent check and balance to all stakeholders. This gave rise to initiatives such as Pharmaledger—a European Union blockchain consortium involving 12 global pharmaceutical firms such as Pfizer, Novartis and GSK.15 In the health care insurance field, peer-to-peer transaction of cryptographically-secured sensitive information between stakeholders would remove costly intermediaries and improve efficacy. Fraudulent activities would also be deterred by the algorithm and the immutable log. This could transform the entire patient-customer journey, from verifiable health declaration during policy purchase to transparent and traceable claims process. It is thus becoming apparent that the trust-less verification and immutable audit trail afforded by blockchain is exceedingly crucial for innovative applications in health care. BLOCKCHAIN TECHNOLOGY IN OPHTHALMOLOGY Ophthalmology as a field has been an early adopter of new evolving technologies, in particular the application of AI and deep learning (DL) for the automated analysis of medical images, such as retinal images and optical coherence tomography scans.16–18 DL in medicine (and ophthalmology), an area of active research, is highly reliant on the availability of large high-quality datasets as well as rigorous model validation and testing. However, the management of diverse datasets from different countries and centers for training and testing of algorithms in these studies poses significant challenges. This is attributable to extensive restrictions due to concerns over data security and patient confidentiality, preventing honest transfer of research medical data to support collaborative efforts.19 In addition, proper research community oversight over the multitude of novel AI and DL systems is unattainable due to a lack of transparency regarding model validation and testing. Recognizing these challenges, in a recent study, Tan et al20 proposed a permission blockchain-enabled platform (based on Hyperledger Fabric) to assist with the development and validation of DL algorithms to tackle the global myopia epidemic. They provide proof-of-concept, using this blockchain-enabled platform for secure handling of data transfer, model sharing, and auditable reporting of model validation and testing results across 3 separate sites in 2 countries, in the development of robust DL algorithms for automated detection of myopic macular degeneration and high myopia from retinal images. They suggest that this blockchain-based solution for the management of research datasets and model testing results provides advantages of data integrity and immutability, as well as automation in data consistency and a shared ledger promoting easier collaboration. They also suggest that widespread adoption of this novel method could increase validity and transparency of AI studies in medicine, and may allow health regulators (eg, US Food and Drug Administration) a means of effectively auditing and verifying the diagnostic performance of AI algorithms for regulatory approval. In conjunction, the immutable transaction log replicated across all nodes provides the ideal digital infrastructure to track each iteration of the AI-model training, improving collaborative efficiency and trust. Further applications of blockchain in the health care industry could likewise impact the field of ophthalmology (Table 2). Supply chain transformation is particularly valuable for perishable products21 and would likely play a significant role in health care, where tight monitoring of labile high-value medications is crucial to guarantee safety and efficacy. Scarce or costly products that require highly regulated storage conditions would be ideal candidates, examples which include total parenteral nutrition, mRNA COVID vaccines, intra-vitreal anti-vascular endothelial growth factors (anti-VEGF), blood products or biologics. During the COVID-19 pandemic, Lin et al established a blockchain-based platform to provide virtual clinical service for ophthalmology patients. They proposed a proof-of-concept to verify and efficiently monitor online prescriptions, creating a blockchain-based online pharmacy for prescription renewals and remote drug delivery.22 The significance of this lies in the fact that telemedicine is a highly visual-dependent service, making it particularly well-suited for visual-oriented specialties like ophthalmology. Another potential application of blockchain in health care, which will be highly relevant in ophthalmology, is the use of blockchain technology to monitor and improve patient treatment adherence as well as to automate medication support programs. This would be particularly valuable for high-cost treatment regimes that require considerable patient compliance, such as recurring intra-vitreal anti-VEGF treatments. TABLE 2 - Blockchain Characteristics and Potential Use Case Immutability31–38 AI algorithm training and testing, health care insurance, data transfer, medication distribution supply chain, patient support programme, medical licensing, patient disease monitoring, clinical drug trial Traceability and provenance31,32,34,37,39 Data transfer, medication distribution supply chain, patient support programme, medical licensing De-centralized data security33–37 Patient support programme, health care insurance, patient disease monitoring, data transfer Peer to peer transaction31–35,37 Health care insurance, data transfer, patient support programmes Cost-less verification33,35,37–40 Health care insurance, patient disease monitoring, patient support programmes, medication distribution supply chain, clinical drug trial Smart contracts/De-centralized autonomous organisations33,35,40,41 Medication distribution supply chain, patient support programmes, health care insurance, Anonymity31,32 Data transfer, patient support programme CHALLENGES Although we expect greater innovative and disruptive use cases for blockchain technology in ophthalmology to materialize, implementation and integration could remain a challenge. First, selecting the appropriate blockchain platform will be critical which, under most health care circumstances, will exclude permissionless blockchains. Researchers, clinicians, and hospital administrators will need to be cognizant of the clinical and operational workflow changes required if blockchain is adopted. Second, mindsets deeply rooted in the traditional DDMS will need to be changed. In addition, switching from DDMS to blockchain will entail greater digital automation, integration of application programming interfaces (API) and distributed applications (Dapps), off and on-chain event connection, wholesale conversion to digitized data collection and upgrading of the information technology infrastructure. Third, there are significant costs. Investments will be required for dedicated digital hardware, networking and storage overheads as well as maintenance. Fourth, from a clinician and provider perspective, immutability of the blockchain platform will prevent amendments of erroneous entries whereas latency could be a source of frustration when contrasted against highly efficient traditional client-server databases. Fifth, blockchain relies on a flawless algorithm to create an asymptotic security, hence cryptographic flaws could leave vulnerabilities within the platform. Finally, data security issues need to be addressed. The decentralized peer-to-peer transaction could potentially compromise patient's data if it has not been appropriately anonymized. The sensitive nature of health care data hence demands that the algorithm undergo extensive trials and penetration tests to guarantee that the patient's privacy and confidentiality is upheld. Finally, the democratization of data sharing at the patient-level might not materialize. It is highly possible that the lure of incentives would be nullified by heightened senses towards privacy preservation, hence failing to convince and motivate patients to proactively share their data. Such inertia could be further compounded by a lack of understanding and trust of the reliability of blockchain platforms. It might be more realistic to consider monetization of big data in an institutional level, yet even that faces significant resistance for fear of privacy breaches or the loss of autonomy over valuable data (Supplementary table: https://links.lww.com/APJO/A87). CONCLUSIONS AND FUTURE DIRECTIONS In conclusion, the health care sector faces a pressing need for new digital technologies that allow secure and efficient sharing of data to address the inefficiencies and demands in current systems. There is increasing recognition that blockchain technology could deliver the novel digital platforms that are required to address these requirements. In the field of ophthalmology, blockchain technology can help to monitor data and results integrity, greater research to support AI In addition, and algorithms are likely to further improve the and of blockchain for widespread health care applications care.
Deploying a mobile edge computing (MEC) server in the mobile blockchain-enabled Internet of things (IoT) system is a promising approach to improve the system performance, however, it imposes a significant challenge on the trust of the MEC server. To address this problem, we first propose an untrusted MEC proof of work (PoW) scheme in mobile blockchain networks where plenty of nonce hash computing demands can be offloaded to the MEC server. Then, we design a nonce ordering algorithm for this scheme to provide fairer computing resource allocation for all mobile IoT devices/users. Specifically, we formulate the user’s nonce selection strategy as a non-cooperative game, where utilities of the individual user are maximized in the untrusted MEC-aided mobile blockchain networks. We also prove the existence of Nash equilibrium and analyze that the cooperation behavior is unsuitable for blockchain-enabled IoT devices by using the repeated game. Finally, we design the blockchain’s difficulty adjustment mechanism to ensure stable block times during a long period of time. Compared with the weighted round-robin algorithm, our proposed nonce ordering algorithm can provide fairer computation resources and optimal nonce selection strategies for all mobile users. Network stability is gained through the proposed blockchain’s difficulty adjustment mechanism. The analysis and optimization results provide valuable design insights for practical mobile blockchain IoT systems.
Mohd Majid Akhtar, Danish Raza Rizvi, Mohd Abdul Ahad, Salil S. Kanhere · 6 authors
A potential rise in interest in the Internet of Things in the upcoming years is expected in the fields of healthcare, supply chain, logistics, industries, smart cities, smart homes, cyber physical systems, etc. This paper discloses the fusion of the Internet of Things (IoT) with the so-called "distributed ledger technology" (DLT). IoT sensors like temperature sensors, motion sensors, GPS or connected devices convey the activity of the environment. Sensor information acquired by such IoT devices are then stored in a blockchain. Data on a blockchain remains immutable however its scalability still remains a challenging issue and thus represents a hindrance for its mass adoption in the IoT. Here a communication system based on IOTA and DLT is discussed with a systematic architecture for IoT devices and a future machine-to-machine (M2M) economy. The data communication between IoT devices is analyzed using multiple use cases such as sending DHT-11 sensor data to the IOTA tangle. The value communication is analyzed using a novel "micro-payment enabled over the top" (MP-OTT) streaming platform that is based on the "pay-as-you-go" and "consumption based" models to showcase IOTA value transactions. In this paper, we propose an enhancement to the classical "masked authenticated message" (MAM) communication protocol and two architectures called dual signature masked authenticated message (DSMAM) and index-based address value transaction (IBAVT). Further, we provided an empirical analysis and discussion of the proposed techniques. The implemented solution provides better address management with secured sharing and communication of IoT data, complete access control over the ownership of data and high scalability in terms of number of transactions that can be handled.
Zhonghua Zhang, Xifei Song, Lei Liu, Jie Yin · 6 authors
Blockchain constructs a distributed point-to-point system, which is a secure and verifiable mechanism for decentralized transaction validation and is widely used in financial economy, Internet of Things, large data, cloud computing, and edge computing. On the other hand, artificial intelligence technology is gradually promoting the intelligent development of various industries. As two promising technologies today, there is a natural advantage in the convergence between blockchain and artificial intelligence technologies. Blockchain makes artificial intelligence more autonomous and credible, and artificial intelligence can prompt blockchain toward intelligence. In this paper, we analyze the combination of blockchain and artificial intelligence from a more comprehensive and three-dimensional point of view. We first introduce the background of artificial intelligence and the concept, characteristics, and key technologies of blockchain and subsequently analyze the feasibility of combining blockchain with artificial intelligence. Next, we summarize the research work on the convergence of blockchain and artificial intelligence in home and overseas within this category. After that, we list some related application scenarios about the convergence of both technologies and also point out existing problems and challenges. Finally, we discuss the future work.
European Society of Radiology (ESR), Elmar Kotter, Luis Martí‐Bonmatí, Adrian P. Brady · 5 authors
Blockchain can be thought of as a distributed database allowing tracing of the origin of data, and who has manipulated a given data set in the past. Medical applications of blockchain technology are emerging. Blockchain has many potential applications in medical imaging, typically making use of the tracking of radiological or clinical data. Clinical applications of blockchain technology include the documentation of the contribution of different "authors" including AI algorithms to multipart reports, the documentation of the use of AI algorithms towards the diagnosis, the possibility to enhance the accessibility of relevant information in electronic medical records, and a better control of users over their personal health records. Applications of blockchain in research include a better traceability of image data within clinical trials, a better traceability of the contributions of image and annotation data for the training of AI algorithms, thus enhancing privacy and fairness, and potentially make imaging data for AI available in larger quantities. Blockchain also allows for dynamic consenting and has the potential to empower patients and giving them a better control who has accessed their health data. There are also many potential applications of blockchain technology for administrative purposes, like keeping track of learning achievements or the surveillance of medical devices. This article gives a brief introduction in the basic technology and terminology of blockchain technology and concentrates on the potential applications of blockchain in medical imaging.
Open access
Blockchain Technology Applications and Security
Retinal Imaging and Analysis
Artificial Intelligence in Healthcare and Education
The contemporary medical system has a significant inconsistency between privacy issues and health requirements. A Blockchain-based technique to hide medical information and keep it safe is proposed in this study. This will ensure the data is accessible and reliable to study reviews and patients. There is no permission given to uncover patients' private information without providing any explanations to the patients. This proposal would execute distributed consensus between patients and research institutions while they function using the PBFT algorithm. The paper will discuss the security and privacy concerns of the proposed scheme. The proposed work is less expensive than other current ideas in terms of time involved in its implementation, with 150 blocks in almost 60 minutes.
The widespread decentralized applications and Blockchain components significantly boost the security frameworks in many vertical applications and use-cases including different secured payment methods and smart contracts. The integral part of any smart contract is the validation of the stake-holder identity, in general, while ideally being achieved without the third-party involvement. Recent industrial research works introduce the sovereign-identity system, where Blockchain becomes a decentralized component to establish a self-certified identity and to avoid a centralized trust third party. Hence, the classification of distributed transactions with respect to identity validation across several users becomes more challenging, especially because of the massive and sensitive identities that are issued through many users and IoT devices and that are used to validate transactions. In this context, it is important to identify and classify the malicious and non-malicious types of transactions. Our proposed method achieves the target of identity classifications from variety of transaction data. Since different users may have different device usage patterns, the data samples and labels located on any individual device may follow a different distribution, which cannot represent the global data distribution. Therefore, the solution could be bi-focal to compensate the gap. This paper coins the approach of hybridizing the consensus where as to initiate a machine learning mechanism to collect the local data globally through a permission driven and a federated approach. We introduce here a Federated Reinforcement learning to be improvised for distributed independent data as a policy of consortium while binding the proof of consensus more centrally authenticated.
Chinmay Mistry, Urvish Thakker, Rajesh Gupta, Mohammad S. Obaidat · 7 authors
An Artificial Intelligence (AI)-enabled and blockchain-driven Electronic Health Record (EHR) maintenance system has a tremendous potential to facilitate reliable, secure, and robust storage systems for EHRs. Such an EHR system would also facilitate researchers, doctors, and government authorities to access data for research, perform analytics, and help in making well-informed decisions. The Artificial Neural Network (ANN) is employed to classify the patients as potentially COVID-19 positive and potentially COVID-19 negative based on the clinical reports and reports of CT-scan. The data of potentially COVID-19 positive patients is stored on blockchain employing InterPlanetary File System (IPFS) protocol. The accessibility of EHR can be done by authorized entities post verification and validation of entities. We analyze the performance of various AI-based algorithms employing metrics such as loss curve, accuracy, etc. for the task of predicting the patient’s potential COVID-19 infection. The 6G network significantly mitigates the network latency and reliability issues and also facilitates the real-time transmission of information. The amount of data generated is pretty high amidst this pandemic and so we employed IPFS protocol which suffices to be a cost-effective solution, moreover satisfying all are stringent requirements. At last, we evaluate the network, security, and storage performance of our architecture MedBlock, which outperformed other state-of-the-art systems.
Clinical trials are the cornerstone of treatment discovery because they provide comprehensive scientific evidence on the safety, efficacy, and optimal use of therapeutics. However, current clinical trials are facing multiple challenges such as patient recruitment, data capture, and overall management. There are various causes of patient recruitment challenges such as inefficient advertising models, complex protocols, and distant trial sites. Data inconsistency is the main challenge of the data capture process. Source data verification, a standard method used for data monitoring, is resource-intensive that can cost up to 25 percent of the total budget. The current clinical trial management system market is fragmented and lacks thorough designs with all desired features so that nearly all respondents to management systems from the annual global survey reported dissatisfaction with the current management system. Based on these challenges, disruptive technologies such as blockchain may provide feasible solutions by utilizing its unique features. Blockchain is an open-source distributed ledger technology that was first applied in the financial sector. Its features such as public audibility, data security, immutability, anonymity, and smart contracts are a good fit for the needs of many healthcare applications. However, there are several common challenges of blockchain technology so that most blockchain designs for healthcare applications are still in the early stage of implementation. This dissertation aims at optimizing clinical trials by developing multiple applications using blockchain technology to provide feasible solutions to the current challenges. We will use real-world data to conduct large-scale simulations to evaluate the feasibility and performance of proposed blockchain models for clinical trial applications.
Ali J. Al-Musharaf, Saif Al-Alak, Haider M. Al-Mashhadi
Blockchain is a decentralized database that stores a growing chain of blocks formed and secured by the consensus of a network node. Blockchain technology is a solution to applications and smart programs so that no third party (peer-to-peer network) is required to store and verify transactions in a safe and reliable manner, such as cryptocurrencies, smart contracts, health care, and the Internet of things (IoT). However, this technology suffers from some limitations, such as network latency and slow transaction validation. In this paper, the proposed method is implemented and discussed by improving the topology of the peer-to-peer blockchain structure to a decentralized topology (structured topology in clusters). This aims to speed up transactions broadcasting time, as well as to reduce the enormous time for nodes consensus mechanism to validate transactions through the intra- and inter-cluster parallel mining in the Proof of Work (PoW) mechanism. The test results demonstrate the feasibility of the proposed method in reducing the consensus time, as well as improve the scalability of the network.
Munavwar Shaikh, Charles Shibu, Enrico Angeles, Deepa Pavithran
Data storage in IoT systems describe how data is pushed from the sensor and where it will be stored. In Bitcoin, there is a limit to the number of transactions that can be stored in the block, similarly in Ethereum it is limited by the gas limit in block. An IoT infrastructure have several applications that includes a sensor collecting data from physical environment. Storing a large amount data in a blockchain faces several challenges due to the distributed nature of the blockchain, high transaction processing time, and reduced scalability. Hence it is crucial to identify what data should be stored and how to store it in a secure way. In this paper, we provide how data is being stored in various blockchain based IoT applications and provides data storage compliance in treating IoT data in a blockchain environment.
BACKGROUND: By 2050, almost 5 billion people globally are projected to have myopia, of whom 20% are likely to have high myopia with clinically significant risk of sight-threatening complications such as myopic macular degeneration. These are diagnoses that typically require specialist assessment or measurement with multiple unconnected pieces of equipment. Artificial intelligence (AI) approaches might be effective for risk stratification and to identify individuals at highest risk of visual loss. However, unresolved challenges for AI medical studies remain, including paucity of transparency, auditability, and traceability. METHODS: In this retrospective multicohort study, we developed and tested retinal photograph-based deep learning algorithms for detection of myopic macular degeneration and high myopia, using a total of 226 686 retinal images. First we trained and internally validated the algorithms on datasets from Singapore, and then externally tested them on datasets from China, Taiwan, India, Russia, and the UK. We also compared the performance of the deep learning algorithms against six human experts in the grading of a randomly selected dataset of 400 images from the external datasets. As proof of concept, we used a blockchain-based AI platform to demonstrate the real-world application of secure data transfer, model transfer, and model testing across three sites in Singapore and China. FINDINGS: The deep learning algorithms showed robust diagnostic performance with areas under the receiver operating characteristic curves [AUC] of 0·969 (95% CI 0·959-0·977) or higher for myopic macular degeneration and 0·913 (0·906-0·920) or higher for high myopia across the external testing datasets with available data. In the randomly selected dataset, the deep learning algorithms outperformed all six expert graders in detection of each condition (AUC of 0·978 [0·957-0·994] for myopic macular degeneration and 0·973 [0·941-0·995] for high myopia). We also successfully used blockchain technology for data transfer, model transfer, and model testing between sites and across two countries. INTERPRETATION: Deep learning algorithms can be effective tools for risk stratification and screening of myopic macular degeneration and high myopia among the large global population with myopia. The blockchain platform developed here could potentially serve as a trusted platform for performance testing of future AI models in medicine. FUNDING: None.
In this digital era, where business operations and customer expectations involve harnessing and sharing the required information. In such scenarios, the trust and barrier for creating trusted partner networks can be resolved by Blockchain technologies. Blockchain has become vital for real-world applications involving business transactions where data security is predominant. Healthcare sector is another application of Blockchain gaining momentum. As countries across the globe grapple under the effect of the COVID-19 pandemic, the healthcare sector is the worst hit domain and hence, should scale like never before. During the current pandemic crisis, Blockchain technology could play a pivotal role in revolutionizing the way medical data can be handled and secured over its decentralized peer-to-peer network, thus enhancing the security of health-care information exchange. The infected patients serve as assets in the proposed Blockchain approach and their records include previous ailments if any, as blocks. In this paper a low-cost Blockchain approach has been proposed to store and view patient status along with transaction log details pertaining to their COVID-19 medical conditions. This secure data can only be viewed by the concerned government and local authorities for monitoring and further action.
Abstract It is irrefutable that blockchain and artificial intelligence (AI) paradigms are spreading at an incredible rate. The two paradigms have distinctive level of innovative nature and multidimensional business propositions. Blockchain innovation can robotize instalments to grant a way for exchanging personal records, information, and logs in a secure, and decentralized manner and can be revealed digitally in the digital currency era. As of late, blockchain and AI are two of the most trending technologies. Blockchain can administer connections among members with no mediator via smart contracts. AI, then, offers insight and dynamic capacities for machines just like people. In this survey, we provide a comprehensive overview about the applications of AI in blockchain. We audit, and sum up the rise of blockchain applications, and stages explicitly focusing on the AI research area. We likewise recognize and summarize open challenges in using blockchain and AI techniques. We also classify the effect of the cloud with these two innovations with respect to the computerized economy, which includes Blockchain as a Cloud and Blockchain as a Service. We moreover survey difficulties and issues identified while provisioning these technologies. It has been found that the integration of AI and blockchain is trusted to make various prospects. Such techniques provide scientists and authorities with an accuracy of up to 90% when taken properly into consideration.
With the advancement of online payments in various products and services, the likelihood of credit card fraud has risen compared to the decades-long history of credit cards. When blockchain systems' immutability meets smart contracts, third-party removal and decentralization could be met as a high level of security. Proposed blockchain with fraud detection technology will assist to mitigate fraudulent credit card transactions due to its intermediate parties. Authors propose a solution (B-Box.com) where credit card transactions are modeled on a blockchain so that the credit card processing can be decentralized and verifiable with an accredited set of computing nodes. This solution reduces fraud due to ambiguous contracts with the use of a smart contract between the bank and the customer. Also, this project includes a scaling mechanism to blockchain because the current projects have a lack of scalability. Moreover, the solution introduces a proactive anomaly detection to detect fraudulent credit card transactions, in which the system will resist frauds before the fraudulent transaction enters the blockchain. So the proposed solution will make transparency between the banks and the end-users and at the same time prevents frauds before it happens which helps the banks to save millions in otherwise lost due to fraud.
Wireless resources, such as spectrum, computation, infrastructures and so on, are critical in 6G and beyond. Dynamic Resource Sharing (DRS), which improves the resource utilization compared to the static and fixed resource allocation, thus needs to be further exploited. Blockchain and AI are two promising techniques for DRS in 6G and beyond. In this article, a blockchain and AI-empow-ered DRS architecture is proposed, where block-chain is used to achieve the functionalities in DRS with improved distribution, security and automation, and AI is implemented to improve the performance of pattern recognition and decision-making in DRS. Finally, a case study where dynamic spectrum sharing is implemented within the proposed architecture, and deep reinforcement learning is used and shown to optimize the profit ratio of the users.
Blockchain is a considered to be a disruptive technology as like an Internet. The features of blockchain are giving more expectations in their applications. IoT is emerging day by day with millions of connecting devices. Even though IoT is evolving, the security of the internet of things is questionable with its architecture. IoT relay on a centralized server is vulnerable to the data breach. The trust in the centralized architecture is also questionable. We require the decentralized technology for IoT to secure their communication. The blockchain is a peer to peer, decentralized, distributed network that does not support the centralized architecture where the data are stored in the common ledger. The cryptographic hash is used in the blockchain which provides the feature of tamper-proof to the blockchain. Bitcoin is the first application that proves the security of blockchain in payment systems. Blockchain is providing transparency in the network with the shared ledger. To avoid the issues in the IoT environment the suggestion from every researcher is to go for blockchain. In this paper, we are going to survey the blockchain adaptability in various IoT environments for finding future research to improve the application of blockchain with IoT.
Blockchain has been a breakthrough in the technology since the last decade and is anticipated as the go-to thing due to features presented by it. The features such as secure, immutable, transparent, and anonymous makes Blockchain technology the frontrunner in the untrustworthy distributed environment. The driving force behind the Blockchain technology are the consensus algorithms that are at the heart of any Blockchain technology. These algorithms determine the security and performance of any Blockchain. The most popular consensus algorithm is the Proof-of-Work which was first used in the Bitcoin. Since then, a number of consensus algorithms have been proposed. This paper presents a brief overview of the Blockchain Technology and popular cryptocurrencies based on Blockchain. Next, the most popular consensus algorithms in the context of Blockchain and cryptocurrencies are discussed.
Blockchain Technology Applications and Security
Advanced Steganography and Watermarking Techniques
Healthcare is one of the most crucial components of our lives since the value of our well-being is immeasurable. The current healthcare system, unfortunately, lacks quality service, accessibility and ease of use. Hence, this paper proposes a smart healthcare system to solve the existing issues of this system. Blockchain-based smart contracts are used to secure sensitive information and maintain the privacy aspect. Smart contracts create an environment in which a significant amount of operations become hands-free. This results in resource-friendliness because the system becomes less reliant on manual labor. The information stored is proven to be accurate, immutable and requires the approval of proper authorities in all cases. Along with this healthcare becomes secure, decentralized, automated and accessible to all.