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ConTra Preference Language: Privacy Preference Unification via Privacy Interfaces

  • After the enactment of the GDPR in 2018, many companies were forced to rethink their privacy management in order to comply with the new legal framework. These changes mostly affect the Controller to achieve GDPR-compliant privacy policies and management.However, measures to give users a better understanding of privacy, which is essential to generate legitimate interest in the Controller, are often skipped. We recommend addressing this issue by the usage of privacy preference languages, whereas users define rules regarding their preferences for privacy handling. In the literature, preference languages only work with their corresponding privacy language, which limits their applicability. In this paper, we propose the ConTra preference language, which we envision to support users during privacy policy negotiation while meeting current technical and legal requirements. Therefore, ConTra preferences are defined showing its expressiveness, extensibility, and applicability in resource-limited IoT scenarios. In addition, we introduce aAfter the enactment of the GDPR in 2018, many companies were forced to rethink their privacy management in order to comply with the new legal framework. These changes mostly affect the Controller to achieve GDPR-compliant privacy policies and management.However, measures to give users a better understanding of privacy, which is essential to generate legitimate interest in the Controller, are often skipped. We recommend addressing this issue by the usage of privacy preference languages, whereas users define rules regarding their preferences for privacy handling. In the literature, preference languages only work with their corresponding privacy language, which limits their applicability. In this paper, we propose the ConTra preference language, which we envision to support users during privacy policy negotiation while meeting current technical and legal requirements. Therefore, ConTra preferences are defined showing its expressiveness, extensibility, and applicability in resource-limited IoT scenarios. In addition, we introduce a generic approach which provides privacy language compatibility for unified preference matching.show moreshow less

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Metadaten
Author:Stefan BecherORCiD, Armin GerlORCiD
URN:urn:nbn:de:bvb:739-opus4-11218
DOI:https://doi.org/10.3390/s22145428
ISSN:1424-8220
Parent Title (English):Sensors
Publisher:MDPI
Place of publication:Basel, Switzerland
Editor:Giuseppe Maria Luigi Sarne, Jianhua Ma, Domenico Rosaci, Gautam Srivastava
Document Type:Article
Language:English
Year of Completion:2022
Year of Completion:2022
Date of first Publication:2022/07/20
Publishing Institution:Universität Passau
Release Date:2023/03/27
Tag:GDPR; legal factors; preference language; privacy; usability
Volume:22
Issue:14
Page Number:18 Seiten
Institutes:Fakultät für Informatik und Mathematik
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 000 Informatik, Informationswissenschaft, allgemeine Werke
open_access (DINI-Set):open_access
Funding Acknowledgement:Gefördert durch den Open-Access-Publikationsfonds der Universitätsbibliothek Passau.
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International