SeFra: A Secure Framework to Manage eHealth Records Using Blockchain Technology
01 Jan 2020-International Journal of E-health and Medical Communications (IGI Global)-Vol. 11, Iss: 1, pp 1-16
TL;DR: The proposed work provides a secure framework to manage the eHealth record by using blockchain (SeFra), where a temporal shadow is used and the integrity of health records is ensured by blockchain technology.
Abstract: Electronic health information is an efficient technique for providing health care services to society. Patient health information is stored in the cloud, to allow access of eHealth information from anywhere, and at any time, but the technical problems are security, privacy, etc. Sharing the medical data in a trustless environment is overcome by the proposed framework SeFra. The proposed work provides a secure framework to manage the eHealth record by using blockchain (SeFra). For authentication purposes, a temporal shadow is used and the integrity of health records is ensured by blockchain technology.
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TL;DR: The first systematic review on blockchain-based personal health records (PHRs) is presented in this paper, where the authors examine the current landscape, design choices, limitations, and future directions of blockchainbased PHRs, and reveal that although research interest in blockchain PHRs is increasing and that the space is maturing, this technology is still largely in the conceptual stage.
Abstract: Background: Blockchain technology has the potential to enable more secure, transparent, and equitable data management. In the health care domain, it has been applied most frequently to electronic health records. In addition to securely managing data, blockchain has significant advantages in distributing data access, control, and ownership to end users. Due to this attribute, among others, the use of blockchain to power personal health records (PHRs) is especially appealing.
Objective: This review aims to examine the current landscape, design choices, limitations, and future directions of blockchain-based PHRs.
Methods: Adopting the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-analyses) guidelines, a cross-disciplinary systematic review was performed in July 2020 on all eligible articles, including gray literature, from the following 8 databases: ACM, IEEE Xplore, MEDLINE, ScienceDirect, Scopus, SpringerLink, Web of Science, and Google Scholar. Three reviewers independently performed a full-text review and data abstraction using a standardized data collection form.
Results: A total of 58 articles met the inclusion criteria. In the review, we found that the blockchain PHR space has matured over the past 5 years, from purely conceptual ideas initially to an increasing trend of publications describing prototypes and even implementations. Although the eventual application of blockchain in PHRs is intended for the health care industry, the majority of the articles were found in engineering or computer science publications. Among the blockchain PHRs described, permissioned blockchains and off-chain storage were the most common design choices. Although 18 articles described a tethered blockchain PHR, all of them were at the conceptual stage.
Conclusions: This review revealed that although research interest in blockchain PHRs is increasing and that the space is maturing, this technology is still largely in the conceptual stage. Being the first systematic review on blockchain PHRs, this review should serve as a basis for future reviews to track the development of the space.
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34 citations
TL;DR: In this paper , the authors focused on data pertinent to diabetic retinopathy disease and its prediction, and used the SqueezeNet classifier to predict the occurrence of diabetic Retinopathy (DR) disease.
Abstract: Blockchain technology has gained immense momentum in the present era of information and digitalization and is likely to gain extreme popularity among the next generation, with diversified applications that spread far beyond cryptocurrencies and bitcoin. The application of blockchain technology is prominently observed in various spheres of social life, such as government administration, industries, healthcare, finance, and various other domains. In healthcare, the role of blockchain technology can be visualized in data-sharing, allowing users to choose specific data and control data access based on user type, which are extremely important for the maintenance of Electronic Health Records (EHRs). Machine learning and blockchain are two distinct technical fields: machine learning deals with data analysis and prediction, whereas blockchain emphasizes maintaining data security. The amalgamation of these two concepts can achieve prediction results from authentic datasets without compromising integrity. Such predictions have the additional advantage of enhanced trust in comparison to the application of machine learning algorithms alone. In this paper, we focused on data pertinent to diabetic retinopathy disease and its prediction. Diabetic retinopathy is a chronic disease caused by diabetes and leads to complete blindness. The disease requires early diagnosis to reduce the chances of vision loss. The dataset used is a publicly available dataset collected from the IEEE data port. The data were pre-processed using the median filtering technique and lesion segmentation was performed on the image data. These data were further subjected to the Taylor African Vulture Optimization (AVO) algorithm for hyper-parameter tuning, and then the most significant features were fed into the SqueezeNet classifier, which predicted the occurrence of diabetic retinopathy (DR) disease. The final output was saved in the blockchain architecture, which was accessed by the EHR manager, ensuring authorized access to the prediction results and related patient information. The results of the classifier were compared with those of earlier research, which demonstrated that the proposed model is superior to other models when measured by the following metrics: accuracy (94.2%), sensitivity (94.8%), and specificity (93.4%).
4 citations
TL;DR: This paper focuses on ensuring the integrity of the health record with context-based Merkle tree (CBMT) through temporal shadow with general public ledger (GPL) and personalized micro ledger (PML).
Abstract: The patient's health record is sensitive and confidential information. The sharing of health information is a first venture to make health services more productive and improve the quality of healthcare services. Decentralized online ledgers with blockchain-based platforms were already proposed and in use to address the interoperability and privacy issues. However, other challenges remain, in particular, scalability, usability, and accessibility as core technical challenges. The paper focuses on ensuring the integrity of the health record with context-based Merkle tree (CBMT) through temporal shadow. In this system, two ledgers were used to ensure the integrity of eHealth records like general public ledger (GPL) and personalized micro ledger (PML). The context-based Merkle tree (CBMT) is used to aggregates all the transactions at a particular time. The context means it depends on time, location, and identity. This is ensured without the help of a third party.
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TL;DR: An App (called Healthcare Data Gateway (HGD) architecture based on blockchain is proposed to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private.
Abstract: Healthcare data are a valuable source of healthcare intelligence. Sharing of healthcare data is one essential step to make healthcare system smarter and improve the quality of healthcare service. Healthcare data, one personal asset of patient, should be owned and controlled by patient, instead of being scattered in different healthcare systems, which prevents data sharing and puts patient privacy at risks. Blockchain is demonstrated in the financial field that trusted, auditable computing is possible using a decentralized network of peers accompanied by a public ledger. In this paper, we proposed an App (called Healthcare Data Gateway (HGD)) architecture based on blockchain to enable patient to own, control and share their own data easily and securely without violating privacy, which provides a new potential way to improve the intelligence of healthcare systems while keeping patient data private. Our proposed purpose-centric access model ensures patient own and control their healthcare data; simple unified Indicator-Centric Schema (ICS) makes it possible to organize all kinds of personal healthcare data practically and easily. We also point out that MPC (Secure Multi-Party Computing) is one promising solution to enable untrusted third-party to conduct computation over patient data without violating privacy.
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TL;DR: This paper introduces blockchain technologies, including their benefits, pitfalls, and the latest applications, to the biomedical and health care domains and discusses the potential challenges and proposed solutions of adopting blockchain technologies in biomedical/health care domains.
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Abstract: Cloud data provenance is metadata that records the history of the creation and operations performed on a cloud data object. Secure data provenance is crucial for data accountability, forensics and privacy. In this paper, we propose a decentralized and trusted cloud data provenance architecture using blockchain technology. Blockchain-based data provenance can provide tamper-proof records, enable the transparency of data accountability in the cloud, and help to enhance the privacy and availability of the provenance data. We make use of the cloud storage scenario and choose the cloud file as a data unit to detect user operations for collecting provenance data. We design and implement ProvChain, an architecture to collect and verify cloud data provenance, by embedding the provenance data into blockchain transactions. ProvChain operates mainly in three phases: (1) provenance data collection, (2) provenance data storage, and (3) provenance data validation. Results from performance evaluation demonstrate that ProvChain provides security features including tamper-proof provenance, user privacy and reliability with low overhead for the cloud storage applications.
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TL;DR: A secure system for PSN-based healthcare using blockchain technique, an improved version of the IEEE 802.15.6 display authenticated association, and a protocol suite to study protocol runtime and other factors are proposed.
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292 citations
Proceedings Article•
01 Jan 2017TL;DR: A framework on managing and sharing EMR data for cancer patient care using blockchain to significantly reduce the turnaround time for EMR sharing, improve decision making for medical care, and reduce the overall cost is proposed.
Abstract: Electronic medical records (EMRs) are critical, highly sensitive private information in healthcare, and need to be frequently shared among peers. Blockchain provides a shared, immutable and transparent history of all the transactions to build applications with trust, accountability and transparency. This provides a unique opportunity to develop a secure and trustable EMR data management and sharing system using blockchain. In this paper, we present our perspectives on blockchain based healthcare data management, in particular, for EMR data sharing between healthcare providers and for research studies. We propose a framework on managing and sharing EMR data for cancer patient care. In collaboration with Stony Brook University Hospital, we implemented our framework in a prototype that ensures privacy, security, availability, and fine-grained access control over EMR data. The proposed work can significantly reduce the turnaround time for EMR sharing, improve decision making for medical care, and reduce the overall cost.
247 citations