A Privacy-Enhanced Multi-Dimensional Fusion Data Identification Method for Healthcare Data

QI Junfeng; XIA Qi; MA ying; LI Shurui; GUAN Qingxu; XIA Hu; GAO Jianbin

doi:10.11959/j.issn.2096-0271.BDR26208

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A Privacy-Enhanced Multi-Dimensional Fusion Data Identification Method for Healthcare Data

更新时间：2026-09-24

- A Privacy-Enhanced Multi-Dimensional Fusion Data Identification Method for Healthcare Data
- Big Data Research (2026)
- 作者机构：
  
  1.电子科技大学计算机科学与工程学院，四川成都 610054
  2.国家信息中心，北京 100045
  3.四川省大数据中心，四川成都 610041
  4.Provincial Big Data Center, Chengdu 610041, China
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.BDR26208
  CLC： TP309
- Received：26 May 2026，
  
  Revised：2026-06-19，
  
  Accepted：24 September 2026，
- 稿件说明：
移动端阅览
QI Junfeng, XIA Qi, MA ying, et al. A Privacy-Enhanced Multi-Dimensional Fusion Data Identification Method for Healthcare Data[J/OL]. Big Data Research, 2026.
DOI：

QI Junfeng, XIA Qi, MA ying, et al. A Privacy-Enhanced Multi-Dimensional Fusion Data Identification Method for Healthcare Data[J/OL]. Big Data Research, 2026. DOI： 10.11959/j.issn.2096-0271.BDR26208.

摘要

针对区域医疗联合体跨院数据共享场景中，现有医疗数据标识存在维度单一、隐私保护与数据可用性矛盾、全生命周期安全管控缺失、行业合规适配性不足的问题，提出了一种隐私增强型多维度融合医疗数据标识方法。该方法融合分级分类、隐私保护、溯源管控、权限管控四大核心能力，设计了一体化的定长标识结构；基于国密SM9标识密码算法构建双假名可关联机制，实现了患者身份匿名前提下的跨院诊疗数据的无损关联；结合差分隐私、SM3哈希链与密文策略属性基加密，实现了敏感属性脱敏、全生命周期防篡改溯源与细粒度权限管控。构建了包含诚实但好奇攻击者与恶意攻击者的多攻击者安全模型，完成了方案的安全性归约证明。实验结果表明，在Intel Core i7-9750H处理器环境下，标识生成平均耗时15.310ms，方案在满足安全性需求的同时具备工程可行性。经与现有方案对比分析，该方案在匿名性、抗合谋攻击、国密适配等方面具有显著优势，符合《数据安全法》《个人信息保护法》及医疗数据安全相关国家标准。

Abstract

In the context of cross-hospital data sharing within regional medical consortia

existing medical data identifier schemes exhibit several critical limitations: single-dimensional structures

the inherent trade-off between privacy and data utility

a lack of lifecycle security governance

and inadequate compliance with industry regulations. To address these challenges

a privacy-enhanced

multi-dimensional fused medical data identifier method is proposed. The scheme integrates four core capabilities—data classification

privacy protection

traceability

and access control—into a unified

fixed-length identifier structure. Leveraging the national cryptographic SM9 identity-based algorithm

we construct a linkable dual-pseudonym mechanism that enables lossless linkage of cross-institutional health records while preserving patient anonymity. By synergistically combining differential privacy

an SM3-based hash chain

and Ciphertext-Policy Attribute-Based Encryption (CP-ABE)

the scheme achieves sensitive attribute obfuscation

tamper-evident lifecycle traceability

and fine-grained access control. A multi-attacker security model

including honest-but-curious and malicious adversaries is established

and a formal security proof for the scheme via security reduction is provided. Experimental results

conducted on an Intel Core i7-9750H processor

show an average identifier generation time of 15.310 ms

demonstrating the scheme's engineering feasibility while meeting stringent security requirements. A comparative analysis reveals that our approach offers significant advantages in anonymity

collusion resistance

and compatibility with national cryptographic standards. The scheme is designed to be compliant with China's Data Security Law

Personal Information Protection Law

and relevant national standards for medical data security.

关键词

Keywords

references

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