Abstract

The Conventional Cloud Common Data Model (CDM) uses a centralized method of user identification and credentials. This needs to be solved in a decentralized way because there are limitations in interoperability such as closed identity management and identity leakage. In this paper, we propose a DID (Decentralized Identifier)-based cloud CDM that allows researchers to securely store medical research information by authenticating their identity and to access the CDM reliably. The proposed service model is used to provide the credential of the researcher in the process of creating and accessing CDM data in the designed secure cloud. This model is designed on a DID-based user-centric identification system to support the research of enrolled researchers in a cloud CDM environment involving multiple hospitals and laboratories. The prototype of the designed model is an extension of the encrypted CDM delivery method using DID and provides an identification system by limiting the use cases of CDM data by researchers registered in cloud CDM. Prototypes built for agent-based proof of concept (PoC) are leveraged to enhance security for researcher use of ophthalmic CDM data. For this, the CDM ID schema and ID definition are described by issuing IDs of CDM providers and CDM agents, limiting the IDs of researchers who are CDM users. The proposed method is to provide a framework for integrated and efficient data access control policy management. It provides strong security and ensures both the integrity and availability of CDM data.

Highlights

  • Today, the key issue of medical services is moving forward from treatment to prevention and management of diseases [1]

  • This paper describes the application of decentralized identifiers (DID) to prove user identity in the cloud Common Data Model (CDM) environment

  • We present a study on blockchain technology for user identity management of medical data and a model for cross-institutional CDM data access control

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Summary

Introduction

The key issue of medical services is moving forward from treatment to prevention and management of diseases [1]. Medical institutions and companies have been promoting technology development in related fields to provide services based on artificial intelligence and big data technology using medical data [2,3,4]. Since each hospital uses a different structure of Hospital Information System (HIS), the need for a CDM is recognized for systematic data management and integrated research [5]. CDM is a data structure defined to efficiently utilize hospitals’ data. It is composed based on international standard terms and has different components depending on the purpose

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