DICON: A Domain-Independent Consent Management for Personal Data Protection
The development of technology accelerated the digital transformation of information systems. As a consequence of this digitization, data became available at any time and in any place. However, despite this ease of data accessibility, persons’ privacy concerns and threats to data privacy h...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9881506/ |
| _version_ | 1828231346733973504 |
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| author | Emre Olca Ozgu Can |
| author_facet | Emre Olca Ozgu Can |
| author_sort | Emre Olca |
| collection | DOAJ |
| description | The development of technology accelerated the digital transformation of information systems. As a consequence of this digitization, data became available at any time and in any place. However, despite this ease of data accessibility, persons’ privacy concerns and threats to data privacy have emerged. Thus, serious privacy problems arise while collecting, storing, accessing, sharing, and archiving personal data. Consent management aims to prevent these problems by preserving privacy and protecting personal data. Hence, there are international treaties and legal regulations for personal data protection which state that consent is required to collect, store, manage and share personal data. In this study, a Semantic Web-based personal consent management model is proposed to protect personal data privacy. The proposed model is domain-independent and aims to control and manage the consent of a person. In order to provide the privacy protection of personal data, the proposed model allows individuals to establish their privacy preferences by determining who can access their personal information, for what purposes, and under what circumstances. For this purpose, a group of ontology is created to ensure the informed consent process. The proposed consent management model is generic. As similar to general personal information, personal health information is also sensitive and must be protected from data leakage. Therefore, the proposed generic model is implemented with Semantic Web technologies and demonstrated for the healthcare domain. |
| first_indexed | 2024-04-12T19:02:52Z |
| format | Article |
| id | doaj.art-153e436fe4bb44879e4130f29ccefea6 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-12T19:02:52Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-153e436fe4bb44879e4130f29ccefea62022-12-22T03:20:06ZengIEEEIEEE Access2169-35362022-01-0110954799549710.1109/ACCESS.2022.32049709881506DICON: A Domain-Independent Consent Management for Personal Data ProtectionEmre Olca0Ozgu Can1https://orcid.org/0000-0002-8064-2905Department of Software Engineering, Maltepe University, Istanbul, TurkeyDepartment of Computer Engineering, Ege University, Izmir, TurkeyThe development of technology accelerated the digital transformation of information systems. As a consequence of this digitization, data became available at any time and in any place. However, despite this ease of data accessibility, persons’ privacy concerns and threats to data privacy have emerged. Thus, serious privacy problems arise while collecting, storing, accessing, sharing, and archiving personal data. Consent management aims to prevent these problems by preserving privacy and protecting personal data. Hence, there are international treaties and legal regulations for personal data protection which state that consent is required to collect, store, manage and share personal data. In this study, a Semantic Web-based personal consent management model is proposed to protect personal data privacy. The proposed model is domain-independent and aims to control and manage the consent of a person. In order to provide the privacy protection of personal data, the proposed model allows individuals to establish their privacy preferences by determining who can access their personal information, for what purposes, and under what circumstances. For this purpose, a group of ontology is created to ensure the informed consent process. The proposed consent management model is generic. As similar to general personal information, personal health information is also sensitive and must be protected from data leakage. Therefore, the proposed generic model is implemented with Semantic Web technologies and demonstrated for the healthcare domain.https://ieeexplore.ieee.org/document/9881506/Consentdata protectionknowledge-based systemsknowledge representationontologyprivacy |
| spellingShingle | Emre Olca Ozgu Can DICON: A Domain-Independent Consent Management for Personal Data Protection IEEE Access Consent data protection knowledge-based systems knowledge representation ontology privacy |
| title | DICON: A Domain-Independent Consent Management for Personal Data Protection |
| title_full | DICON: A Domain-Independent Consent Management for Personal Data Protection |
| title_fullStr | DICON: A Domain-Independent Consent Management for Personal Data Protection |
| title_full_unstemmed | DICON: A Domain-Independent Consent Management for Personal Data Protection |
| title_short | DICON: A Domain-Independent Consent Management for Personal Data Protection |
| title_sort | dicon a domain independent consent management for personal data protection |
| topic | Consent data protection knowledge-based systems knowledge representation ontology privacy |
| url | https://ieeexplore.ieee.org/document/9881506/ |
| work_keys_str_mv | AT emreolca diconadomainindependentconsentmanagementforpersonaldataprotection AT ozgucan diconadomainindependentconsentmanagementforpersonaldataprotection |