@article{BecherGerl2022, author = {Becher, Stefan and Gerl, Armin}, title = {ConTra Preference Language: Privacy Preference Unification via Privacy Interfaces}, series = {Sensors}, volume = {22}, journal = {Sensors}, number = {14}, editor = {Sarne, Giuseppe Maria Luigi and Ma, Jianhua and Rosaci, Domenico and Srivastava, Gautam}, publisher = {MDPI}, address = {Basel, Switzerland}, issn = {1424-8220}, doi = {10.3390/s22145428}, url = {http://nbn-resolving.de/urn:nbn:de:bvb:739-opus4-11218}, pages = {18 Seiten}, year = {2022}, abstract = {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 a generic approach which provides privacy language compatibility for unified preference matching.}, language = {en} }