Security-Aware and Privacy-Preserving Personal Health Record Sharing Using Consortium Blockchain

Wang, Yong; Zhang, Aiqing; Zhang, Peiyun; Qu, Youyang; Yu, Shui

doi:10.1109/jiot.2021.3132780

Cited by 42 publications

(45 citation statements)

References 55 publications

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“…To develop Personal Health Records capable of being shared without having their security compromised and privacy leaked, Y. Wang et al presented in [33] a blockchainbased PHR management and sharing system using a consortium blockchain (Hyperledger Fabric) and InterPlanetary File system technology. The IPFS technology is used to store the PHR encrypted information of the IoMT.…”

Section: Related Workmentioning

confidence: 99%

“…In this work, the main objective was to grasp the possibility of implementing a system integrating m-health with blockchain technology with methods for health data traceability while keeping anonymity and enabling the promotion of health data ownership. To accomplish the defined objectives, an analysis of the mechanisms and systems that use an integration of blockchain with m-health systems or that attempt to improve EHR systems using blockchain was conducted [1] [33]. Based on this analysis, it was clear enough that the proposed system should have a database component, to store off-chain data impossible to store in the blockchain itself, a blockchain component, to use the advantageous capabilities of blockchain for immutable transactions control and an Application/API to enabling the communication between the user and both of the other components.…”

Section: Conclusion and Future Work A Conclusionmentioning

confidence: 99%

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A System for the Promotion of Traceability and Ownership of Health Data Using Blockchain

2022

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The advent of wireless technologies and the development of more and better globally connected mobile devices, leverage real time health monitoring. Mobile health (m-health) promise to deliver health services anytime and anywhere, improving user convenience and enabling faster diagnoses without the need to travel to healthcare facilities. The use of m-health applications on mobile devices with the support of cloud computing is nowadays a technology trend that has many advantages, but also poses several challenges, especially on the data storage and privacy. Blockchain technology is an exponentially growing technology used in various research areas from finance, voting mechanisms, production chains, among others. This technology provides important characteristics such as immutability, non-repudiation, transparency, and reducing the need for intermediaries. Hence, this paper presents a novel approach for blockchain technology applied to m-health systems. This proposal allows an easy and fast integration with other health systems or applications allowing a patient-user to access his electronic health record in a more secure way. The data is traceable throughout the system, however maintaining the necessary anonymity. Hence, a prototype for a blockchain-based solution using Hyperledger Fabric was developed. This implementation enables the creation of a chronologically organized and immutable health data record. To create an anonymous storage system, the proposed system uses two separate database components that maintain data traceability through sets of IDs stored in the blockchain. Furthermore, the development of the proposed system was evaluated in terms of performance and network configurations of the Hyperledger Fabric.

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Section: Related Workmentioning

confidence: 99%

Section: Conclusion and Future Work A Conclusionmentioning

confidence: 99%

A System for the Promotion of Traceability and Ownership of Health Data Using Blockchain

2022

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“…x Accuracy and privacy: Over the IoMT environment, medical data can be accessed by various malicious actors as it presents huge security concerns regarding confidentiality, integrity, and accuracy. Due to attack intrusion [34], the medical data may get lost or altered. Therefore, a well-developed method, such as an intrusion detection system, must be implemented to maintain the accuracy and privacy of data.…”

Section: Challenges and Further Researchmentioning

confidence: 99%

An Overview on Security and Privacy of Data in IoMT Devices: Performance Metrics, Merits, Demerits, and Challenges

Khatiwada

Yang

2022

Studies in Health Technology and Informatics

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The Internet of Medical Things (IoMT) emerges with new trendsetter device applications, where it defines the incorporation of medical devices with the Internet of Things (IoT). The healthcare sector continues to encounter challenging obstacles that have an impact on the quality of treatment provided to patients. To get rid of this problem, IoMT is being deployed to achieve the high reliability and efficiency of the health system. The IoMT devices are superimposed with clinical information as they contain the details of patient health data, address, and other patient identifiers. By containing such amount of sensitive information, it becomes cumbersome to preserve data privacy and security. Due to inadequate security and privacy precautions, patient health data is susceptible to leakage, which has a direct impact on the patient’s life. In addition, the majority of medical devices are susceptible to cyberattacks, putting patient information at risk. Inadequate control of life-support equipment can have a devastating effect on patient outcomes. Thus, this survey intends to review the various security models of IoMT devices using standard techniques to support health care systems. It provides a wide range of literature reviews regarding IoMT systems and compares them with traditional methodologies. This review work exhibits the motivation for current technologies to maintain the security and privacy of patients’ data with IoMT devices. The systematic review entails background on security in IoMT devices, techniques for security, usage of diverse validation measures, and also discusses the problems and motivation for future research work.

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“…Propose a consortium blockchain-based Personal Health Records (PHR) and sharing scheme that is security-aware and privacy-preserving, as motivated by [36]. For Medica IoT (MIoT)'s PHR symmetric encryption storage, we use the Interplanetary File System (IPFS).…”

Section: Security and Privacymentioning

confidence: 99%

IoT-Based Patient Health Data Using Improved Context-Aware Data Fusion and Enhanced Recursive Feature Elimination Model

Saranya

Fatima

2022

IEEE Access

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The Internet of Things (IoT) in the healthcare market is propelled forward by the implementation of digital systems for monitoring and analysing health problems. IoT and smart devices can contribute to a highly smart environment. Smart medical devices interconnected with smartphone apps can collect medical and other required health data. "Data Fusion (DF)" refers to integrating data and knowledge from multiple sources. However, these techniques are also applied to other domains, including text processing. Using data from multiple distributed sources, the objective of DF in multisensory contexts is to reduce the chance of detection errors and increase their reliability. The objective is to increase scalability, performance efficiency, and identification. A medical device's ability to scale up or down demonstrates its capacity to respond to environmental factors. A more scalable system performs as expected, with no interruptions, and makes the best available use of the resource management it has. To ensure that these tracking devices all work the same way, it is essential to form a specialised group to develop uniformity in areas such as communication channels, aggregation of data, and smart interfaces. The main contribution of this research is pre-processing, DF using the Improved Context-aware Data Fusion (ICDF) algorithm, feature extraction via Improved Principal Component Analysis (IPCA), feature selection through the Enhanced Recursive Feature Elimination (ERFE) algorithm, and a classifier using an ensemble-based Machine Learning (ML) model. The Improved Dynamic Bayesian Network (IDBN) is a good trade-off for tractability, becoming a tool for ICDF operations. The simulation results show that the proposed ICDF model achieves higher performance in terms of 97% accuracy, 96% precision, 97% recall, and 97% F1 score in the healthcare system.

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Security-Aware and Privacy-Preserving Personal Health Record Sharing Using Consortium Blockchain

Cited by 42 publications

References 55 publications

A System for the Promotion of Traceability and Ownership of Health Data Using Blockchain

A System for the Promotion of Traceability and Ownership of Health Data Using Blockchain

An Overview on Security and Privacy of Data in IoMT Devices: Performance Metrics, Merits, Demerits, and Challenges

IoT-Based Patient Health Data Using Improved Context-Aware Data Fusion and Enhanced Recursive Feature Elimination Model

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