A Semantically Rich Knowledge Graph to Automate HIPAA Regulations for Cloud Health IT Services
dc.contributor.author | Kim, Dae-young Leroy | |
dc.contributor.author | Joshi, Karuna | |
dc.date.accessioned | 2021-08-06T19:31:43Z | |
dc.date.available | 2021-08-06T19:31:43Z | |
dc.date.issued | 2021-05-15 | |
dc.description | 7th IEEE International Conference on Big Data Security on Cloud (BigDataSecurity 2021) | en_US |
dc.description.abstract | As healthcare organizations adopt cloud-based services to manage their patient data, compliance with the rules and policies of the Health Insurance Portability and Accountability Act (HIPAA) regulation becomes increasingly complex. At present, HIPAA rules are available only in large textual format and require significant human effort to implement in the Health IT systems. Moreover, every change in the regulation, like the recent relaxation in telehealth policy due to the COVID-19 pandemic, has to be manually implemented in the IT system. We have developed a semantically rich Knowledge graph, using Semantic Web technologies to represent HIPAA rules in a machine-processable format. This will significantly help in automatically reasoning of HIPAA policies. In this paper, we describe our design along with the results of our study of the current status of research on HIPAA ontology. We have validated our design against use cases defined by the US Department of Health and Human Services (HHS). This knowledge graph can be integrated with existing healthcare systems to provide automated compliance with HIPAA policies. | en_US |
dc.description.uri | https://ieeexplore.ieee.org/document/9463546 | en_US |
dc.format.extent | 6 pages | en_US |
dc.genre | conference papers and proceedings | en_US |
dc.genre | preprints | en_US |
dc.identifier | doi:10.13016/m2spjr-ighg | |
dc.identifier.citation | D. -y. Kim and K. P. Joshi, "A Semantically Rich Knowledge Graph to Automate HIPAA Regulations for Cloud Health IT Services," 2021 7th IEEE 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), 2021, pp. 7-12, doi: 10.1109/BigDataSecurityHPSCIDS52275.2021.00013. | en_US |
dc.identifier.uri | http://hdl.handle.net/11603/22336 | |
dc.identifier.uri | https://doi.org/10.1109/BigDataSecurityHPSCIDS52275.2021.00013 | |
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 | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | en_US |
dc.rights | © 2021 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. | |
dc.subject | UMBC Ebiquity Research Group | en_US |
dc.title | A Semantically Rich Knowledge Graph to Automate HIPAA Regulations for Cloud Health IT Services | en_US |
dc.type | Text | en_US |
dcterms.creator | https://orcid.org/0000-0002-6354-1686 | en_US |