提出FHIR资源访问图模型，可精准识别医疗系统并发访问中的三类竞态漏洞。
Analyzing Healthcare Interoperability Vulnerabilities: Formal Modeling and Graph-Theoretic Approach
- 构建基于图论的FRAG模型，用节点和带类型边表示并发进程与资源访问
- 在1500条模拟日志中实现90.0%的F1分数，较基线提升64.5个百分点
- 适用于医疗系统安全审计、FHIR平台开发人员及医疗信息安全研究人员
在医疗环境中，基于HL7 FHIR的互操作平台允许多个独立系统（如电子病历、药房、检验系统和设备）并发异步访问共享患者资源。然而，FHIR规范缺乏并发控制协议，现有研究仅关注操作系统内核的竞态条件，或仅针对认证与注入攻击，将并发访问视为顺序处理。为此，本文提出形式化定义的FHIR资源访问图（FRAG），其结构为G = (P,R,E, λ, τ, S)，其中节点代表并发进程，带类型的边表示资源访问事件，竞态条件则作为可检测的结构特征。文中正式定义了三类临床相关竞态：同时写冲突（SWC）、TOCTOU授权违规（TAV）和级联更新竞态（CUR）。FRAG模型被实现为三遍图遍历检测算法，并在1,500条合成的FHIR R4事务日志上与基于时间窗口的基线方法对比。在完全并发访问（C2）条件下，FRAG的F1得分达90.0%，远超基线的25.5%，提升64.5个百分点。
原文摘要 · Abstract (English)
In a healthcare environment, the healthcare interoperability platforms based on HL7 FHIR allow concurrent, asynchronous access to a set of shared patient resources, which are independent systems, i.e., EHR systems, pharmacy systems, lab systems, and devices. The FHIR specification lacks a protocol for concurrency control, and the research on detecting a race condition only targets the OS kernel. The research on FHIR security only targets authentication and injection attacks, considering concurrent access to patient resources to be sequential. The gap in the research in this area is addressed through the introduction of FHIR Resource Access Graph (FRAG), a formally defined graph G = (P,R,E, λ, τ, S), in which the nodes are the concurrent processes, the typed edges represent the resource access events, and the race conditions are represented as detectable structural properties. Three clinically relevant race condition classes are formally specified: Simultaneous Write Conflict (SWC), TOCTOU Authorization Violation (TAV), and Cascading Update Race (CUR). The FRAG model is implemented as a three-pass graph traversal detection algorithm and tested against a time window-based baseline on 1,500 synthetic FHIR R4 transaction logs. Under full concurrent access (C2), FRAG attains a 90.0% F1 score vs. 25.5% for the baseline, a 64.5 pp improvement.
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