DICON: A Domain-Independent Consent Management for Personal Data Protection

Abstract

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. 16 17 users. In [2], consent management is stated as one of the most 50 important concepts in the Future Internet. Furthermore, it is 51 stated that the Future Internet is going to see a lot of lawsuits 52 that deal with what service a person has consented to, what 53 scope that consent had, and how the service has evolved after 54 the consent was given. Therefore, obtaining the consent of 55 the user and managing the process of this consent is very 56 important for the security and privacy of personal data.57 The consent information needs to be maintained and shared 58 by multiple parties such as the data subject, the data con-59 troller, data processor, and data protection authorities [3]. 60 Hence, the consent information needs to be represented 61 in a meaningful way to provide interoperability between 62 these parties. Also, users must be able to create, revoke 63 and update their consents. Consequently, an efficient consent 64 management system has inevitable importance to preserve 65 user privacy. For this purpose, a domain-independent consent 66 management model for preserving personal data privacy is 67 proposed in this study. The proposed consent management 68 model is based on the Semantic Web which is an extension 69 of the current web. In the Semantic Web, information is 70 given in a well-defined meaning to represent information 71 more meaningfully for both humans and computers [4]. Thus, 72 the Semantic Web provides interoperability which is the 73 ability to exchange informa...

A Consent-Based Privacy-Compliant Personal Data-Sharing System

“…Olca and Can [19] proposed a semantic web-based domainindependent consent management method. By utilizing the proposed ontology models for consent management, service users are able to protect their personal data according to informed consent.…”