Performance analysis of a private blockchain network built on Hyperledger Fabric for healthcare

Al-Sumaidaee, Ghassan; Alkhudary, Rami; Žilić, Željko; Swidan, Andraws

doi:10.1016/j.ipm.2022.103160

Cited by 36 publications

(28 citation statements)

References 36 publications

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“…Another benefit is that it has a high transaction throughput and low transaction cost. Hyperledger Fabric is the most sophisticated Blockchain framework available compared to other Blockchain frameworks 140,141 Zero‐knowledge proof (ZKP) …”

Section: Discussionmentioning

confidence: 99%

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Securing AI‐based healthcare systems using blockchain technology: A state‐of‐the‐art systematic literature review and future research directions

Shinde,

Patil,

Kotecha

et al. 2023

Trans Emerging Tel Tech

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Healthcare institutions are progressively integrating artificial intelligence (AI) into their operations. The extraordinary potential of AI is restricted by insufficient medical data for AI model training and adversarial attacks wherein attackers perturb the dataset by adding some noise to it, which leads to the malfunctioning of the AI models, and a lack of trust caused by the opaque operational approach it employs. This Systematic Literature Review (SLR) is a state‐of‐the‐art survey of the research on blockchain technology for securing AI‐integrated healthcare applications. The most relevant articles from the Scopus and Web of Science (WoS) databases were identified using the PRISMA model. Most of the existing literature is about protecting the healthcare data used by AI‐based healthcare systems using blockchain technology, but the modality of data (text, images, audio, and sound) was not specifically mentioned. Information on protecting the training phase and model deployment for AI‐based healthcare systems considering the variations in feature extraction based on the modality of data was also not clearly specified. Hence, the three subfields of AI, namely, natural language processing (NLP), computer vision, and acoustic AI are further studied to identify security loopholes in its implementation pipeline. The three phases, namely the dataset, the training phase, and the trained models need to be protected from adversaries to avoid malfunctioning of the deployed AI models. The nature of the data processed by NLP, computer vision, and acoustic AI, underlying deep neural network (DNN) architectures, the complexity of attacks, and the perceivability of attacks by humans are analyzed to identify the need for security. A blockchain solution for AI‐based healthcare systems is synthesized based on the findings that have demonstrated the distinctive technological features of blockchains. It offers a solution for the privacy and security issues encountered by NLP, computer vision, and acoustic AI to boost the widespread adoption of AI applications in healthcare.

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Section: Discussionmentioning

confidence: 99%

“…Hyperledger Fabric is the most sophisticated Blockchain framework available compared to other Blockchain frameworks. 140,141 III. Zero-knowledge proof (ZKP) Zero-Knowledge Proof (ZKP) has been used as one of the most effective methods for meeting transaction secrecy requirements.…”

Section: Hyperledgermentioning

confidence: 99%

Securing AI‐based healthcare systems using blockchain technology: A state‐of‐the‐art systematic literature review and future research directions

Shinde,

Patil,

Kotecha

et al. 2023

Trans Emerging Tel Tech

View full text Add to dashboard Cite

show abstract

“…Another related issue is scalability as more organizations or hospitals join the network. Certain experiments in healthcare 21 have only a very basic structure of blockchain implementation with a maximum of two medical organizations joining a single channel. Therefore, there is no proof of absolute latency test performed in networks implemented in this sector.…”

Section: Healthcare Use Casementioning

confidence: 99%

“…This is done to understand the maximum capacity of the network. The experiment is benchmarked against two popular experiments by Xu et al 22 and Al-Sumaidaee et al Al-Sumaidaee et al 21 have performed a Hyperledger Fabric experiment using the concept of just two medical institutions and performed latency analysis of the network.…”

Section: Experiments and Performance Analysismentioning

confidence: 99%

Scalability Performance Analysis of Blockchain Using Hierarchical Model in Healthcare

Sadath, MSc, MCA,

Mehrotra,

Kumar

2024

BHTY

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Blockchain technology has emerged as a pivotal point to enhance privacy and security in enterprise applications and cyber world. However, scalability is an issue researcher are grappling with, in large enterprises, especially in organizations bearing multiple levels of hierarchy and access privilege. Therefore, the existing models and consensus algorithms suffer one way or another. The medical or healthcare sector suffers this problem the most due to the huge amount of data and probably the central point of failure of the traditional database management system. This paper addresses the situation through a hierarchical model in Hyperledger fabric enterprise application through a healthcare sector use case. Multiple organizations are added to each hierarchy considering them as different organization levels (Hospitals, Hospital Governance, and Insurance company). Currently the first implementation has two levels of hierarchy to show networks of hospitals joining an Insurance Company. Our primary experiment revolves around this model to test and enhance the performance of the network. Performance of the model is assessed by varying and scaling environmental parameters such as the number of organizations, transaction numbers, channels, block intervals and block sizes. The benchmarking tool used is Hyperledger caliper to test various indicators such as success and failure rates along with throughput and latency. The current work only tests the scalability of the model with patient data.

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“…Various types of sensitive data contained in the Electronic Health Record (EHR) are regarded as one the privacy issues that make patients not interested in sharing their data [4]. The fact also states that one hospital with another does not necessarily have a compatible system, so it has profound implications for patients, especially in medical record data [5].…”

Section: Introductionmentioning

confidence: 99%

Private Blockchain in the Field of Health Services

Purwono

Nisa

Wibisono

et al. 2023

JAHIR

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Blockchain is a technology that is quite popular and has been adopted in various fields in recent years. This technology has caught the attention of researchers in the health sector because of its innovation which is considered capable of providing the necessary guarantees for the safe processing, sharing, and management of sensitive patient data. There are many problems with falsifying reports and withholding important information from patients, which is considered medical fraud. Hyperledger, a type of private Blockchain, is very suitable for healthcare applications. A private blockchain is a restricted type of blockchain network created by an entity. This type of network is limited to those with access permissions. In addition, private blockchains usually use a centralized verification system and are controlled by the network's creators. Hyperledger Fabric is one example of a permissioned blockchain that can play a role in implementing patient-centric, interoperable healthcare systems

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Performance analysis of a private blockchain network built on Hyperledger Fabric for healthcare

Cited by 36 publications

References 36 publications

Securing AI‐based healthcare systems using blockchain technology: A state‐of‐the‐art systematic literature review and future research directions

Securing AI‐based healthcare systems using blockchain technology: A state‐of‐the‐art systematic literature review and future research directions

Scalability Performance Analysis of Blockchain Using Hierarchical Model in Healthcare

Private Blockchain in the Field of Health Services

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