Semantically Rich Differential Access to Secure Cloud HER
dc.contributor.author | Walid, Redwan | |
dc.contributor.author | Joshi, Karuna Pande | |
dc.contributor.author | Choi, SeungGeol | |
dc.date.accessioned | 2023-06-07T20:08:14Z | |
dc.date.available | 2023-06-07T20:08:14Z | |
dc.date.issued | 2023-05-26 | |
dc.description | 9th IEEE International Conference on Big Data Security on Cloud (Big Data Security 2023), New York, NY, May 6-8, 2023. | en_US |
dc.description.abstract | 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. | en_US |
dc.description.sponsorship | This work has been supported by Office of Naval Research under grants N00014-18-1-2453, N00014-19-WX-00568, and N00014-20-WX01704 and by NSF grant 1955319. | en_US |
dc.description.uri | https://ieeexplore.ieee.org/document/10132149 | en_US |
dc.format.extent | 9 pages | en_US |
dc.genre | conference papers and proceedings | en_US |
dc.genre | preprints | en_US |
dc.identifier | doi:10.13016/m2bi8z-wobg | |
dc.identifier.citation | R. Walid, K. P. Joshi and S. Geol Choi, "Semantically Rich Differential Access to Secure Cloud EHR," 2023 IEEE 9th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), New York, NY, USA, 2023, pp. 1-9, doi: 10.1109/BigDataSecurity-HPSC-IDS58521.2023.00012. | |
dc.identifier.uri | http://hdl.handle.net/11603/28128 | |
dc.identifier.uri | https://doi.org/10.1109/BigDataSecurity-HPSC-IDS58521.2023.00012 | |
dc.language.iso | en_US | en_US |
dc.publisher | IEEE | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Information Systems Department Collection | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.relation.ispartof | UMBC Student Collection | |
dc.rights | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
dc.subject | UMBC Ebiquity Research Group | en_US |
dc.title | Semantically Rich Differential Access to Secure Cloud HER | en_US |
dc.type | Text | en_US |
dcterms.creator | https://orcid.org/0000-0002-1303-0909 | en_US |
dcterms.creator | https://orcid.org/0000-0002-6354-1686 | en_US |