IoT-Reg: A Comprehensive Knowledge Graph for Real-Time IoT Data Privacy Compliance

dc.contributor.authorEchenim, Kelvin
dc.contributor.authorJoshi, Karuna
dc.date.accessioned2023-12-15T15:21:48Z
dc.date.available2023-12-15T15:21:48Z
dc.date.issued2023-12-15
dc.descriptionIEEE Big Data 2023, 3rd Workshop on Knowledge Graphs and Big Data, 15-18 December 2023, Sorrento, Italy
dc.description.abstractThe proliferation of the Internet of Things (IoT) has led to an exponential increase in data generation, especially from wearable IoT devices. While this data influx offers unparalleled insights and connectivity, it also brings significant privacy and security challenges. Existing regulatory frameworks like the United States (US) National Institute of Standards and Technology Interagency or Internal Report (NISTIR) 8228, the US Health Insurance Portability and Accountability Act (HIPAA), and the European Union (EU) General Data Protection Regulation (GDPR) aim to address these challenges but often operate in isolation, making their compliance in the vast IoT ecosystem inconsistent. This paper presents the IoT-Reg ontology, a holistic semantic framework that amalgamates these regulations, offering a stratified approach based on the IoT data lifecycle stages and providing a comprehensive yet granular approach to IoT data handling practices. The IoT-Reg ontology aims to transform the IoT domain into a realm where regulatory controls are seamlessly integrated system components by emphasizing risk management, compliance, and the pivotal role of manufacturers’ privacy policies, ensuring consistent adherence, enhancing user trust, and promoting a privacy-centric IoT environment. We include the results of validating this framework against risk mitigation for Wearable IoT devices.
dc.description.sponsorshipThis research was partially supported by the NSF award 1747724, Phase I IUCRC UMBC: Center for Accelerated Real time Analytics (CARTA).
dc.description.urihttps://ieeexplore.ieee.org/document/10386545
dc.format.extent10 pages
dc.genreconference papers and proceedings
dc.genrepreprints
dc.identifier.citationEchenim, Kelvin Uzoma, and Karuna Pande Joshi. “IoT-Reg: A Comprehensive Knowledge Graph for Real-Time IoT Data Privacy Compliance.” In 2023 IEEE International Conference on Big Data (BigData), 2897–2906, 2023. https://doi.org/10.1109/BigData59044.2023.10386545.
dc.identifier.urihttp://hdl.handle.net/11603/31110
dc.language.isoen_US
dc.publisherIEEE
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Information Systems Department Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Center for Accelerated Real Time Analysis
dc.rights© 2024 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.subjectUMBC Ebiquity Research Group
dc.titleIoT-Reg: A Comprehensive Knowledge Graph for Real-Time IoT Data Privacy Compliance
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0002-6354-1686

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