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Background As digital healthcare services handle increasingly more sensitive health data, robust access control methods are required. Especially in emergency conditions, where the patient’s health situation is in peril, different healthcare providers associated with critical cases may need to be granted permission to acquire access to Electronic Health Records (EHRs) of patients. The research objective of this work is to develop a proactive access control method that can grant emergency clinicians access to sensitive health data, guaranteeing the integrity and security of the data, and generating trust without the need for a trusted third party. Methods A contextual and blockchain-based mechanism is proposed that allows access to sensitive EHRs by applying prognostic procedures where information based on context, is utilized to identify critical situations and grant access to medical data. Specifically, to enable proactivity, Long Short Term Memory (LSTM) Neural Networks (NNs) are applied that utilize patient’s recent health history to prognose the next two-hour health metrics values. Fuzzy logic is used to evaluate the severity of the patient’s health state. These techniques are incorporated in a private and permissioned Hyperledger-Fabric blockchain network, capable of securing patient’s sensitive information in the blockchain network. Results The developed access control method provides secure access for emergency clinicians to sensitive information and simultaneously safeguards the patient’s well-being. Integrating this predictive mechanism within the blockchain network proved to be a robust tool to enhance the performance of the access control mechanism. Furthermore, the blockchain network of this work can record the history of who and when had access to a specific patient’s sensitive EHRs, guaranteeing the integrity and security of the data, as well as recording the latency of this mechanism, where three different access control cases are evaluated. This access control mechanism is to be enforced in a real-life scenario in hospitals. Conclusions The proposed mechanism informs proactively the emergency team of professional clinicians about patients’ critical situations by combining fuzzy and predictive machine learning techniques incorporated in the private and permissioned blockchain network, and it exploits the distributed data of the blockchain architecture, guaranteeing the integrity and security of the data, and thus, enhancing the users’ trust to the access control mechanism.

Background: Electronic Health Record (EHR) systems are used as an efficient and effective technique for sharing patient’s health records among different hospitals and various other key stakeholders of the healthcare industry to achieve better diagnosis and treatment of patients globally. However, the existing EHR systems mostly lack in providing appropriate security, entrusted access control and handling privacy and secrecy issues and challenges in current hospital infrastructures. Objective: To solve this delicate problem, we propose a Blockchain-enabled Hyperledger Fabric Architecture for different EHR systems. Methodology: In our EHR blockchain system, Peer nodes from various organizations (stakeholders) create a ledger network, where channels are created to enable secure and private communication between different stakeholders on the ledger network. Individual patients and other stakeholders are identified and registered on the network by unique digital certificates issued by membership service provider (MSP) component of the fabric architecture. Results: We created and implemented different Chaincodes to handle the business logic for executing separate EHR transactions on the network. The proposed fabric architecture provides a secure, transparent and immutable mechanism to store, share and exchange EHRs in a peer-to-peer network of different healthcare stakeholders. It ensures interoperability, scalability and availability in adapting the existing EHRs for strengthening and providing an effective and secure method to integrate and manage patient records among medical institutions in the healthcare ecosystem.

The focus of this review article is on the societal problems and end user acceptance of blockchain technology. The paper begins by outlining the importance of blockchain in modernizing trust and data management systems and highlighting its rapid spread across numerous industries. In‐depth analysis of the adoption‐influencing aspects is done, which also lists the advantages and typical end‐user problems. It examines the privacy implications, restrictions on pseudonymity, and function of technologies that improve privacy, such as zero‐knowledge proofs, while also exploring the legal and regulatory environment around blockchain, putting a focus on digital identity, intellectual property, and data ownership. It also evaluates blockchain security features, such as flaws and risks associated with smart contracts, discusses best practices for boosting security, discusses the societal effects of blockchain, and makes suggestions for legislators, companies, and scholars. The use of blockchain technology and its effects on privacy, rights, and security are discussed in real‐world case studies as well. This article investigates blockchain technology's complex ecosystem, focusing on its societal impact, end‐user acceptance, and security aspects. It discusses significant determinants of adoption, privacy issues, legal issues, and security issues. Real‐world case studies highlight the applications of blockchain and provide helpful insights for those involved in academics, business, and government.

Blockchain is an emerging technology that can radically improve transactions security at banking, supply chain, and other transaction networks. It's estimated that Blockchain will generate $3.1 trillion in new business value by 2030. Essentially, it provides the basis for a dynamic distributed ledger that can be applied to save time when recording transactions between parties, remove costs associated with intermediaries, and reduce risks of fraud and tampering. This book explores the fundamentals and applications of Blockchain technology. Readers will learn about the decentralized peer-to-peer network, distributed ledger, and the trust model that defines Blockchain technology. They will also be introduced to the basic components of Blockchain (transaction, block, block header, and the chain), its operations (hashing, verification, validation, and consensus model), underlying algorithms, and essentials of trust (hard fork and soft fork). Private and public Blockchain networks similar to Bitcoin and Ethereum will be introduced, as will concepts of Smart Contracts, Proof of Work and Proof of Stack, and cryptocurrency including Facebook's Libra will be elucidated. Also, the book will address the relationship between Blockchain technology, Internet of Things (IoT), Artificial Intelligence (AI), Cybersecurity, Digital Transformation and Quantum Computing. Readers will understand the inner workings and applications of this disruptive technology and its potential impact on all aspects of the business world and society. A look at the future trends of Blockchain Technology will be presented in the book.

This paper examines the benefits and constraints of applying blockchain technology for the Paris Agreement carbon market mechanism and develops a list of technical requirements and soft factors as selection criteria to test the feasibility of two different blockchain platforms. The carbon market mechanism, as outlined in Article 6.2 of the Paris Agreement, can accelerate climate action by enabling cooperation between national Parties. However, in the past, carbon markets were limited by several constraints. Our research investigates these constraints and translates them into selection criteria to design a blockchain platform to overcome these past limitations. The developed selection criteria and assumptions developed in this paper provide an orientation for blockchain assessments. Using the selection criteria, we examine the feasibility of two distinct blockchains, Ethereum and Hyperledger Fabric, for the specific use case of Article 6.2. These two blockchain systems represent contrary forms of design and governance; Ethereum constitutes a public and permissionless blockchain governance system, while Hyperledger Fabric represents a private and permissioned governance system. Our results show that both blockchain systems can address present carbon market constraints by enhancing market transparency, increasing process automation, and preventing double counting. The final selection and blockchain system implementation will first be possible, when the Article 6 negotiations are concluded, and governance preferences of national Parties are established. Our paper informs about the viability of different blockchain systems, offers insights into governance options, and provides a valuable framework for a concrete blockchain selection in the future.

The performance of a permissioned blockchain, namely, Hyperledger Fabric, is modeled and analyzed in a quantitative manner in this paper. Various types of nodes contribute to the performance of Hyperledger Fabric, and each of those is modeled and tracked along the operational flow of the permissioned blockchain. There are nodes for endorsement, ordering, and commitment to realize the due decentralized network operations. A quantitative model for each type of nodes has been proposed in Ke and Park (Performance study on various Hyperledger Fabric node types and transaction flow, IEEE BCCA, 2021) along with numerical analysis. Each type of the nodes is characterized in terms of transaction/block queue size and waiting time, and the transaction/block arrival rates and the transaction/block service rates are considered for simulation purposes. The analysis is extended beyond the analysis in Ke and Park (Performance study on various Hyperledger Fabric node types and transaction flow, IEEE BCCA, 2021) in this paper to particularly demonstrate how the arrival rates and the service rates co-influence the performance and how the number of channels impacts the performance, in order to ultimately facilitate a more dynamic way of optimization, taking the co-relation across different types of nodes into account. The major contribution of this paper to the field of computer science by creating a series of queuing models to evaluate the performance of different types of nodes: Chaincode Execution and Endorsement, Block Creation and Delivery, Transaction Validation and Block Committing, and Transaction Processing.

The spread of crypto-currencies globally has led to blockchain technology receiving greater attention in recent times. This paper focuses more broadly on the uses of ledger databases as a traditional database manager. Ledger databases will be examined within the parameters of two categories. The first of these are Centralized Ledger Databases (CLD)-based Centralised Ledger Technology (CLT), of which LedgerDB will be discussed. The second of these are Permissioned Blockchain Technology-based Decentralised Ledger Technology (DLT) where Hyperledger Fabric, FalconDB, BlockchainDB, ChainifyDB, BigchainDB, and Blockchain Relational Database will be examined. The strengths and weaknesses of the reviewed technologies will be discussed, alongside a comparison of the mentioned technologies.

The term “blockchain” originally refers to the underlying technology used in implementing the Bitcoin protocol and network based on a paper published by Satoshi Nakamoto in 2008. The present-day use of this term generally refers, in a broad stroke, to a myriad of nascent distributed ledger technologies that are either associated with or evolved from the invention of Bitcoin. This writing seeks to provide the readers with some guidance on technological considerations when deciding to apply blockchain for commercial use.