T-RBAC Model Based on Two-Dimensional Dynamic Trust Evaluation under Medical Big Data

Rong Jiang,Yang Xin,Huiping Cheng,Wenxuan Wu,M Hassaballah

doi:10.1155/2021/9957214

Rong Jiang, Yang Xin + Show 3 more

Open Access

https://doi.org/10.1155/2021/9957214

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Abstract

The professionalism and complexity of medical big data and the expensiveness of acquiring medical knowledge make it difficult for policymakers to judge whether the information accessed by doctors is necessary from a professional perspective and to formulate accurate access control strategies. To solve the above problems, this paper proposes a T-RBAC (trust-role based access control) model based on two-dimensional dynamic trust assessment, Using AHP and Grey theory to quantify the role attribute trust in the dimension of the doctor’s own attributes, Using Euler’s measurement method and probability statistics to quantify doctors’ behavioral trust in the dimension of historical behavior, then, the trust rule base performs hierarchical authorization based on the comprehensive trust value obtained by the weighted average. Multiattribute trust comprehensive evaluation makes the access control model have finer access granularity and higher security. At the same time, the introduction of time decay function and penalty function enhances the model’s sensitivity, dynamics, and resistance to bleaching attacks.

Highlights

With the development of the new generation of mobile Internet and the Internet of Things, data processing capabilities continue to increase, computing, and storage costs continue to decrease, and networks continue to expand
This paper proposes a two-dimensional dynamic trust ðRT, HTÞ evaluation algorithm based on T-RBAC
How to balance the advantages and disadvantages of medical informatization will become a hot topic in future research

Summary

Introduction

With the development of the new generation of mobile Internet and the Internet of Things, data processing capabilities continue to increase, computing, and storage costs continue to decrease, and networks continue to expand. The popularization of HIS (hospital information system) integrates data scattered in various departments of medical institutions or among medical institutions and stores them in a unified manner, realizes data sharing, facilitates information access, and improves the modern management level and diagnosis and treatment of medical institutions. With the deepening of informatization, medical big data under the background of “Internet + medical” mainly comes from four aspects: patient treatment process (patientcentered data generated during the routine clinical diagnosis and management of the hospital, such as physical sign data, laboratory test data, patient description data, surgical data, and cost data), wearable devices

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