Hernandez, Julio ORCID: 0000-0003-1347-9631, McKenna, Lucy ORCID: 0000-0002-6035-7656 and Brennan, Rob ORCID: 0000-0001-8236-362X (2021) TIKD: A trusted integrated knowledge dataspace for sensitive healthcare data sharing. In: 16th IEEE International Workshop on E-Health Systems & Web Technologies (ESAS 2021)at COMPSAC, 12-16 Jul 2021, Online.
Abstract
This paper presents the Trusted Integrated Knowledge Dataspace (TIKD), a new dataspace, based on linked data technologies and trusted data sharing, that supports integrated knowledge graphs for sensitive application environments such as healthcare. State-of-the-art shared dataspaces do not consider sensitive data and privacy-aware log records as part of their solutions, defining only how to access data. TIKD complements dataspace security approaches through trusted data sharing that considers personal data handling, data privileges, pseudonymization of user activity logging, and privacy-aware data interlinking services. TIKD was implemented on the Access Risk Knowledge(ARK) Platform, a socio-technical risk governance system, and deployed as part of the ARK-Virus Project which aims to govern the risk management of Personal Protection Equipment (PPE)across a group of collaborating healthcare institutions. The ARK Platform was evaluated, both before and after implementing the TIKD, using the ISO 27001 Gap Analysis Tool (GAT) which determines compliance with the information security standard.The results of the evaluation indicated that compliance with ISO 27001 increased from 50% to 85%. The evaluation also provided a set of recommended actions to meet the remaining requirements of the ISO 27001 standard. TIKD provides a collaborative environment, based on knowledge graph integration and GDPR-compliant personal data handling, as part of the data security infrastructure. As a result of this work, a new trusted data security methodology, based on personal data handling,data privileges, access control context specification, and privacy-aware data interlinking, was developed using a knowledge graph approach
Metadata
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Event Type: | Conference |
Refereed: | Yes |
Uncontrolled Keywords: | Dataspace; Knowledge Graph; Trusted Data; Personal Data Handling |
Subjects: | UNSPECIFIED |
DCU Faculties and Centres: | DCU Faculties and Schools > DCU Business School Research Institutes and Centres > ADAPT |
Published in: | 2021 IEEE 45th Annual Computers, Software, and Applications Conference (COMPSAC). . IEEE. |
Publisher: | IEEE |
Official URL: | https://doi.org/10.1109/COMPSAC51774.2021.00280 |
Copyright Information: | © 2021 The Authors |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
Funders: | EU Horizon 2020 |
ID Code: | 25929 |
Deposited On: | 12 Jul 2021 12:01 by Vidatum Academic . Last Modified 16 Jan 2023 16:43 |
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