Improving security of medical big data by using Blockchain technology

Sharma, Pratima; Borah, Malaya Dutta; Namasudra, Suyel

doi:10.1016/j.compeleceng.2021.107529

Cited by 63 publications

(23 citation statements)

References 19 publications

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“…The challenges identified through the review of literature have been classified according to the pre-consultation, consultation and post-consultation stages (shown in Figure 1). In the first stage, the patients may fear the chances of fraud, fake credentials of doctors, delays in appointments and misuse of patients' medical records (Mackey et al, 2020;Sharma et al, 2021). Also, there are chances of errors in managing enormous amounts of medical data by the organizations.…”

Section: Emerging Challenges In Healthcarementioning

confidence: 99%

Conceptualizing the role of blockchain in omnichannel healthcare: a Delphi study

Sangal

Nigam

Bhutani

2022

AJIM

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PurposeThis study aims to identify the challenges in the healthcare industry as it adopts an omnichannel setup in an emerging economy context. Further, the study determines the scope of blockchain in addressing these challenges.Design/methodology/approachThe study uses a qualitative approach to understand the challenges in the omnichannel healthcare industry and know the scope of blockchain in building an omnichannel healthcare system. In the first stage, it did an in-depth analysis of the extant literature, followed by a Delphi study with 24 healthcare experts.FindingsThe study presents the current challenges in the omnichannel healthcare sector in an emerging economy. Further, it develops a novel conceptual framework for blockchain adoption in the omnichannel healthcare industry. The study also presents propositions that will help healthcare service providers enhance decision-making concerning the adoption of blockchain in the healthcare industry.Research limitations/implicationsThe research results may lack generalizability due to the exploratory approach and emerging economies context. Theoretically, in this study, the authors extend the theory of swift trust and organization information processing theory in an omnichannel healthcare context.Practical implicationsThe propositions provided in this paper can help healthcare managers make strategic decisions on the scope of adoption of blockchain for omnichannel healthcare.Originality/valueThis study explores the understudied area of challenges in omnichannel healthcare and the scope of blockchain for omnichannel healthcare in an emerging economy context.

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Section: Emerging Challenges In Healthcarementioning

confidence: 99%

Conceptualizing the role of blockchain in omnichannel healthcare: a Delphi study

Sangal

Nigam

Bhutani

2022

AJIM

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“…Refs. [18][19][20][21][22] suggested a blockchain-enabled healthcare system in which applications are offloaded to their secure workload network for execution. Each patient data transaction is replicated at different nodes and has an immutable process to avoid any attack in the system.…”

Section: Related Workmentioning

confidence: 99%

Potent Blockchain-Enabled Socket RPC Internet of Healthcare Things (IoHT) Framework for Medical Enterprises

Lakhan

Grønli

Majumdar

et al. 2022

Sensors

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Present-day intelligent healthcare applications offer digital healthcare services to users in a distributed manner. The Internet of Healthcare Things (IoHT) is the mechanism of the Internet of Things (IoT) found in different healthcare applications, with devices that are attached to external fog cloud networks. Using different mobile applications connecting to cloud computing, the applications of the IoHT are remote healthcare monitoring systems, high blood pressure monitoring, online medical counseling, and others. These applications are designed based on a client–server architecture based on various standards such as the common object request broker (CORBA), a service-oriented architecture (SOA), remote method invocation (RMI), and others. However, these applications do not directly support the many healthcare nodes and blockchain technology in the current standard. Thus, this study devises a potent blockchain-enabled socket RPC IoHT framework for medical enterprises (e.g., healthcare applications). The goal is to minimize service costs, blockchain security costs, and data storage costs in distributed mobile cloud networks. Simulation results show that the proposed blockchain-enabled socket RPC minimized the service cost by 40%, the blockchain cost by 49%, and the storage cost by 23% for healthcare applications.

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“…In the last two subsections we show how the baseline model and machine learning models with optimal feature sets were modelled. In this subsection, the authors quantitatively analyse the improvements in performance of those machine learning models generated by the optimal feature sets compared to the baseline model [28,29]. The visual differences in accuracy and F1-score can be seen in the bar graph in Figures 7 and 8.…”

Section: Comparison Of Optimal Feature Model With Baseline Modelmentioning

confidence: 99%

Artificial Intelligence for Creating Low Latency and Predictive Intrusion Detection with Security Enhancement in Power Systems

et al. 2021

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Advancement in network technology has vastly increased the usage of the Internet. Consequently, there has been a rise in traffic volume and data sharing. This has made securing a network from sophisticated intrusion attacks very important to preserve users’ information and privacy. Our research focuses on combating and detecting intrusion attacks and preserving the integrity of online systems. In our research we first create a benchmark model for detecting intrusions and then employ various combinations of feature selection techniques based upon ensemble machine learning algorithms to improve the performance of the intrusion detection system. The performance of our model was investigated using three evaluation metrics namely: elimination time, accuracy and F1-score. The results of the experiment indicated that the random forest feature selection technique had the minimum elimination time, whereas the support vector machine model had the best accuracy and F1-score. Therefore, conclusive evidence could be drawn that the combination of random forest and support vector machine is suitable for low latency and highly accurate intrusion detection systems.

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Improving security of medical big data by using Blockchain technology

Cited by 63 publications

References 19 publications

Conceptualizing the role of blockchain in omnichannel healthcare: a Delphi study

Conceptualizing the role of blockchain in omnichannel healthcare: a Delphi study

Potent Blockchain-Enabled Socket RPC Internet of Healthcare Things (IoHT) Framework for Medical Enterprises

Artificial Intelligence for Creating Low Latency and Predictive Intrusion Detection with Security Enhancement in Power Systems

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