A medical big data access control model based on smart contracts and risk in the blockchain environment

Front Public Health. 2024 Mar 28:12:1358184. doi: 10.3389/fpubh.2024.1358184. eCollection 2024.

Abstract

The rapid development of the Hospital Information System has significantly enhanced the convenience of medical research and the management of medical information. However, the internal misuse and privacy leakage of medical big data are critical issues that need to be addressed in the process of medical research and information management. Access control serves as a method to prevent data misuse and privacy leakage. Nevertheless, traditional access control methods, limited by their single usage scenario and susceptibility to single point failures, fail to adapt to the polymorphic, real-time, and sensitive characteristics of medical big data scenarios. This paper proposes a smart contracts and risk-based access control model (SCR-BAC). This model integrates smart contracts with traditional risk-based access control and deploys risk-based access control policies in the form of smart contracts into the blockchain, thereby ensuring the protection of medical data. The model categorizes risk into historical and current risk, quantifies the historical risk based on the time decay factor and the doctor's historical behavior, and updates the doctor's composite risk value in real time. The access control policy, based on the comprehensive risk, is deployed into the blockchain in the form of a smart contract. The distributed nature of the blockchain is utilized to automatically enforce access control, thereby resolving the issue of single point failures. Simulation experiments demonstrate that the access control model proposed in this paper effectively curbs the access behavior of malicious doctors to a certain extent and imposes a limiting effect on the internal abuse and privacy leakage of medical big data.

Keywords: access control; blockchain; medical big data; risk; smart contracts.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Big Data
  • Biomedical Research*
  • Blockchain*
  • Computer Simulation
  • Health Behavior

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Natural Science Foundation of China (Nos. 71972165, 61763048, 72164037), Key Projects of Basic Research for Science and Technology Foundation of Yunnan Province (No. 202001AS070031), the Central Government’s Special Program for Guiding Local Science and Technology Development (No. 202307AB110009).