9th IEEE International Conference on Big Data Security on Cloud (BigDataSecurity 2023)

Semantically Rich Differential Access to Secure Cloud EHR

, , and

Existing Cloud-based Electronic Health Record (EHR) services face challenges in handling heterogeneous data and maintaining performance with large records since they often use a relational database or only partially store information in a graph database. We have developed a novel approach that allows fine-grained field-level security for Cloud EHRs to protect patient privacy and data security. Our graph-based EHR has been developed by integrating Attribute-based Encryption (ABE) with ontology reasoning using Semantic Web technologies. The novelty of our approach lies in providing differential access to an EHR by using a comprehensive knowledge graph that stores all medical data as encrypted nodes, thereby handling heterogeneous patient data while preserving good performance. In this paper, we describe our system in detail, along with the results demonstrating that the system maintains consistent data retrieval performance with different data sizes and allows real-time updates on the data while supporting queries.


  • 536886 bytes
UMBC ebiquity