Semantically Rich Access Control in Cloud EHR Systems Based on MA-ABE
| dc.contributor.author | Dixit, Sharad | |
| dc.contributor.author | Joshi, Karuna Pande | |
| dc.contributor.author | Choi, SeungGeol | |
| dc.contributor.author | Elluri, Lavanya | |
| dc.date.accessioned | 2022-06-27T21:10:40Z | |
| dc.date.available | 2022-06-27T21:10:40Z | |
| dc.date.issued | 2022-06-27 | |
| dc.description | In proceedings of 8th IEEE International Conference on Big Data Security on Cloud (BigDataSecurity 2022) | en_US |
| dc.description.abstract | With the rapid implementation of Cloud-based Electronic Health Record (EHR) systems, health providers are specifically concerned about handling data privacy on the cloud. Existing methods have either scalability issues by requiring that patients grant access to their medical data or a trust issue by having a single authority, thereby creating the problem of a single point of attack. Hence there is a need to develop an EHR system that addresses these bottlenecks for safe, secure, and easy cloud-based EHR management. To address these bottlenecks, we have developed a novel framework that allows policy-based multi-authority access permission to Electronic Health Record systems used by multiple care providers from various places or organizations. This framework, residing on the Edge, has been built using the Multi-Authority Attribute Based Encryption (MA-ABE) and Semantic Web technologies to provide a safe, semantically rich approach to facilitate secure data sharing among organizations who manage different attributes of end-users using a shared dataset. This paper describes our novel approach and the proof of concept prototype that we created to evaluate our framework. | en_US |
| dc.description.sponsorship | This research was supported by the Office of Naval Research and the National Science Foundation. We thank Adam Aviv, Travis Mayberry, and Daniel Roche, and members of the Ebiquity Research Group for their vital feedback. | en_US |
| dc.description.uri | https://ieeexplore.ieee.org/document/9799462 | en_US |
| dc.format.extent | 10 pages | en_US |
| dc.genre | conference papers and proceedings | en_US |
| dc.genre | preprints | en_US |
| dc.identifier | doi:10.13016/m2refj-34rd | |
| dc.identifier.citation | S. Dixit, K. P. Joshi, S. G. Choi and L. Elluri, "Semantically Rich Access Control in Cloud EHR Systems Based on MA-ABE," 2022 IEEE 8th 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), Jinan, China, 2022, pp. 1-10, doi: 10.1109/BigDataSecurityHPSCIDS54978.2022.00012. | |
| dc.identifier.uri | http://hdl.handle.net/11603/25063 | |
| dc.identifier.uri | https://doi.org/10.1109/BigDataSecurityHPSCIDS54978.2022.00012 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| 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 | © 2022 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 | |
| dc.title | Semantically Rich Access Control in Cloud EHR Systems Based on MA-ABE | en_US |
| dc.type | Text | en_US |
| dcterms.creator | https://orcid.org/0000-0002-6354-1686 | en_US |
