VARTE:Trust evaluation model based on VAR for mobile medical information system

Guo, Jingyu; Zhang, Xu

doi:10.1109/bigcom51056.2020.00021

Cited by 2 publications

(1 citation statement)

References 17 publications

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“…Hu et al [24] combined the entropy weight method with fuzzy theory to comprehensively evaluate the interactive trust value, and then used a two-way selection mechanism of roles and a third-party real-time monitoring mechanism to dynamically control access to the healthcare cloud system. The VARTE model [25] is based on vector auto-regressive (VAR) to effectively compute the trust value of user behavior in mobile health information systems. He et al [26] discussed a distributed medical sensor network trust evaluation model, in which nodes can assess the credibility of each other to detect malicious nodes.…”

Section: Trust-based Access Controlmentioning

confidence: 99%

A Blockchain-Based Trustworthy Access Control Scheme for Medical Data Sharing

Wang,

Wu,

Chen

et al. 2024

IET Information Security

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Blockchain is commonly employed in access control to provide safe medical data exchange because of the characteristics of decentralization, nontamperability, and traceability. Patients share personal health data by granting access rights to users or medical institutions. The major purpose of the existing access control techniques is to identify users who are permitted to access medical data. They hardly ever recognize internal assailants from legitimate entities. Medical data will involve multilayer access within the authorized organizations. Considering the cost of permissions management and the problem of insider malicious node attacks, users hope to implement authorization constraints within the authorized institutions. It can prevent their data from being maliciously disclosed by end-users from different authorized healthcare domains. For the purpose to achieve the fine-grained permissions propagation control of medical data in sharing institutions, a trust-based authorization access control mechanism is suggested in this study. Trust thresholds are assigned to different privileges based on their sensitivity and used to generate zero-knowledge proof to be broadcasted among blockchain nodes. This method evaluates the trust of each user through the dynamic trust calculation model. And meanwhile, smart contract is employed to verify whether the user’s trust can activate some permissions and ensure the privacy of the user’s trust in the process of authorization verification. In addition, the authorization transaction between users and institutions is recorded on the blockchain for patient traceability and accountability. The feasibility and effectiveness of the scheme are demonstrated through comprehensive comparisons and extensive experiments.

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Section: Trust-based Access Controlmentioning

confidence: 99%