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Health care professionals are required to maintain accurate health records of patients. Furthermore, these records should be shared across different health care organizations for professionals to have a complete review of medical history and avoid missing important information. Nowadays, health care providers use electronic health records (EHRs) as a key to the implementation of these goals and delivery of quality care. However, there are technical and legal hurdles that prevent the adoption of these systems, such as concerns about performance and privacy issues. This study aimed to build and evaluate an experimental blockchain for EHRs, named HealthChain, which overcomes the disadvantages of traditional EHR systems. HealthChain is built based on consortium blockchain technology. Specifically, three organizations, namely hospitals, insurance providers, and governmental agencies, form a consortium that operates under a governance model, which enforces the business logic agreed by all participants. Every peer node hosts an instance of the distributed ledger consisting of EHRs and an instance of chaincode regulating the permissions of participants. Designated orderers establish consensus on the order of EHRs and then disseminate blocks to peers. HealthChain achieves functional and nonfunctional requirements. It can store EHRs in a distributed ledger and share them among different participants. Moreover, it demonstrates superior features, such as privacy preservation, security, and high throughput. These are the main reasons why HealthChain is proposed. Consortium blockchain technology can help to build new EHR systems and solve the problems that prevent the adoption of traditional systems.

The issue of identity authentication for online medical services has been one of the key focuses of the healthcare industry in recent years. Most healthcare organizations use centralized identity management systems (IDMs), which not only limit the interoperability of patient identities between institutions of healthcare, but also create isolation between data islands. The more important matter is that centralized IDMs may lead to privacy disclosure. Therefore, we propose Health-zkIDM, a decentralized identity authentication system based on zero-knowledge proof and blockchain technology, which allows patients to identify and verify their identities transparently and safely in different health fields and promotes the interaction between IDM providers and patients. The users in Health-zkIDM are uniquely identified by one ID registered. The zero-knowledge proof technology is deployed on the client, which provides the user with a proof of identity information and automatically verifies the user’s identity after registration. We implemented chaincodes on the Fabric, including the upload of proof of identity information, identification, and verification functions. The experiences show that the performance of the Health-zkIDM system can achieve throughputs higher than 400 TPS in Caliper.

Internet of Things (IoT) technology is now widely used in energy, healthcare, services, transportation, and other fields. With the increase in industrial equipment (e.g., smart mobile terminals, sensors, and other embedded devices) in the Internet of Things and the advent of Industry 4.0, there has been an explosion of data generated that is characterized by a high volume but small size. How to manage and protect sensitive private data in data sharing has become an urgent issue for enterprises. Traditional data sharing and storage relies on trusted third-party platforms or distributed cloud storage, but these approaches run the risk of single-node failure, and third parties and cloud storage providers can be vulnerable to attacks that can lead to data theft. To solve these problems, this paper proposes a Hyperledger Fabric blockchain-based secure data transfer scheme for enterprises in the Industrial Internet of Things (IIOT). We store raw data in the IIoT in the InterPlanetary File System (IPFS) network after encryption and store the Keyword-index table we designed in Hyperledger Fabric blockchain, and enterprises share the data by querying the Keyword-index table. We use Fabric’s channel mechanism combined with our designed Chaincode to achieve privacy protection and efficient data transmission while using the Elliptic Curve Digital Signature Algorithm (ECDSA) to ensure data integrity. Finally, we performed security analysis and experiments on the proposed scheme, and the results show that overall the data transfer performance in the IPFS network is generally better than the traditional network, In the case of transferring 5 MB file size data, the transmission speed and latency of IPFS are 19.23 mb/s and 0.26 s, respectively, and the IPFS network is almost 4 times faster than the TCP/IP network while taking only a quarter of the time, which is more advantageous when transferring small files, such as data in the IIOT. In addition, our scheme outperforms the blockchain systems mainly used today in terms of both throughput, latency, and system overhead. The average throughput of our solution can reach 110 tps (transactions are executed per second), and the minimum throughput in experimental tests can reach 101 tps.

It is necessary to identify what factors affect distributed trust and validate their effect on distributed trust and user satisfaction in an area of the food supply chain for sustainable business. The purpose of the present study is to examine determinants of distributed trust in the blockchain-based food supply chain and test seven hypotheses derived from the structural equation model integrating distributed trust, its three determinants, and user satisfaction. Transparency, traceability, and security are suggested as three determinants of distributed trust along the blockchain-based food supply chain. Data were collected from users of Chinese firms employing blockchain-based food supply chains to validate the research model and test the seven hypotheses. The present study contributes to clarifying the significance of distributed trust and suggesting evidence of its role in the food supply chain. The present study discussed trust-free systems based on blockchain technology related to sustainability through the findings.

In distributed environment, a digital transaction or operation requires transparency and trust among multiple stakeholders. Several approches address such issues however, among these blockchain provides a viable solution which has received wide acceptance in the recent past. Permissioned blockchain solutions adopt more efficient consensus algorithms and smart contracts. There are many smart-contract solutions exists (such as, etherium, IBM blockchain, hyperledger fabric), however, much of them mainly follow traditional access control models. A role-based access control model provides controlled access of resources to members. This research work presents an extended usage control model known as DistU (Distributed Usage Control). DistU is proposed to capture all possible access control models required by a business for permissioned blockchain frameworks. DistU can monitor a resource continuously during the operation and update the attributes accordingly, performing different actions, such as denying or revoking permissions. We believe that the proposed DistU usage control model can provide a fine-grained control for blockchain resource management. The paper also contributes to provide a protoype implementation of fine-grained permission model on Hyperledger Fabric. The reason of selecting Fabric for this research is that, it is the first execute-order achitecture blockchain that provides a platform to develop general business applciations. Secondly, it is an opensource operating system of permissioned blockchain with huge industry support.

The performance of blockchains is a critical issue in various applications, such as digital currency transactions and balance checking. Blockchain system architectures such as the Hyperledger Fabric blockchain system (HFBS) have decentralized modular functions, where each module runs on an independent set of hosts. This study conducts a series of experiments to understand the performance limitations of each modular operation in a blockchain system architecture. Three studies involving software programs installed on cloud computing platforms are conducted to evaluate the transaction processing bottleneck. We present an improved modular configuration to enhance the cost efficiency of consortium blockchain systems. Although the CLI module consumes the largest processing resource, the scaled features make the traffic load distributed. The endorsing module is actually bottleneck due to inextensibility and state database. Experimental results obtained from the state database and system performance evaluation indicate that the performance of the state database is highly related to the read-type transactions of the HFBS but not to the write-type transactions. We argue that the performance bottleneck of read operations can be attributed to the fact that CouchDB cannot achieve high system performance under a large number of query operations. When querying the internal text in CouchDB, the system scans the entire data table. Thus, performance and scalability bottlenecks occur for CouchDB. Accordingly, we propose the adoption of MySQL Document Store, which uses a binary storage format similar to that of the state database of HFBS. The experimental results confirm that MySQL Document Store outperforms CouchDB and native state database. The consequent increase in the operational efficiency of the state database enhanced the operational performance of the HFBS. The practical contribution of this study is that its findings can serve as a reference for system structure design for developers and indicate suitable strategies that can be deployed by developers in blockchain systems.

Communication and information technologies have accelerated the implementation of electronic medical records, but at the same time, have put patient privacy, information security and health data at risk. An alternative to address the problem of security and privacy of medical data is the use of blockchain. Scalability has become one of the biggest challenges facing the development of blockchain-based electronic health records (EHRs). The purpose of this article is to implement and test a scalable blockchain-based EHR management system. For this reason, we present a scalable blockchain-based EHR management architecture. In this paper, we propose an EHR management model based on entities and user roles, adapt, and then implement with Hyperledger Fabric in a two-channel configuration. We develop a prototype in Fabric using a one-and two-channel configuration. We then designed and conducted an experiment to verify the performance of the proposed scheme in terms of scalability improvement. This scalable blockchain-based EHR management solution, such as the Hyperledger Fabric platform, offers a viable alternative to address scalability issues, as well as to protect patient’s privacy and the security of their medical data.

Blockchain Technology has grown exponentially in recent years due to its decentralized, immutable, transparent data storage, transaction sharing, and processing capabilities. With the emergence of different blockchain platforms, it is important to analyze and evaluate the performance of these platforms in various scenarios. The popularity of the public blockchain, i.e., Bitcoin and Ethereum, has increased manifold. But in distinction to a public blockchain, there is a permissioned and private blockchain that allows restricted involvement of users in the network. To make a well-informed decision regarding the selection of an appropriate platform for utilization, it is crucial to evaluate diverse performance metrics among the numerous available blockchain platforms. In this study, we assessed the performance of the Hyperledger Fabric blockchain (HLF), taking into account various metrics such as resource consumption, throughput, success rate, and latency. We have incorporated parameters such as the ordering service, programming language to write chaincode/smart contracts, number of transactions, transactions per second, and organizations to evaluate the system’s performance. Along with our analysis, we also suggested potential areas of research for future development of blockchain technology.

In academia, it is essential to verify the integrity and completeness of knowledge, for which an open peer review process is now being conducted by experts in the field. Recently, various open peer review systems have been designed to realize effective open peer review. However, (1) their design principles are not consistent; (2) use cases are rather static and limited; and (3) their implementations have been rarely introduced. To address these issues and realize practical deployment of open peer review systems, in this paper, we present a template for creating a configurable open peer review system. In particular, using the proposed template, an open peer review system operating on Hyperledger Fabric, which allows flexible and dynamic application of various open peer review policies, can be easily instantiated. In addition, by introducing a broker module, all pieces of information in the review process could effectively be handled in both the existing review system currently in operation and the created blockchain-based open peer review system, allowing a gradual transition to the new system. Since the proposed template is embodied based on full implementation and disclosed to the public in the form of an open source, we believe that this work can contribute substantially to the popularization of blockchain-based open peer review systems.

Federated learning is a branch of machine learning where a shared model is created in a decentralized and privacy-preserving fashion, but existing approaches using blockchain are limited by tailored models. We consider the possibility to extend a set of supported models by introducing the oracle service and exploring the usability of blockchain-based architecture. The investigated architecture combines an oracle service with a Hyperledger Fabric chaincode. We compared two logistic regression implementations in Go language—a pure chaincode and an oracle service—at various data (2–32 k instances) and network (3–13 peers) sizes. Experiments were run to assess the performance of blockchain-based model inference using 2D synthetic and EEG eye state datasets for a supervised machine learning detection task. The benchmarking results showed that the impact on performance is acceptable with the median overhead of oracle service reaching 2–4%, depending on the dimensionality of the dataset. The overhead tends to diminish at large dataset sizes with the runtime depending on the network size linearly, where additional peers increased the runtime by 6.3 and 6.6 s for 2D and EEG datasets, respectively. Demonstrated negligible difference between implementations justifies the flexible choice of model in the blockchain-based federated learning and other machine learning applications.