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2020
Conference Paper
Titel
Modelling and Presentation of Privacy-Relevant Information for Internet Users
Abstract
Privacy policies are the state of the practice technique for data transparency. Oftentimes, however, they are presented in a non-prominent way, are lengthy, and are not written in the users' language. As a result, their acceptance is rather low, even though users are generally interested in privacy. Thus, we need enhanced transparency approaches. In this paper, we present a taxonomy and models that allow to describe privacy-relevant information. These models are based on practical privacy policies and legal regulations, and enable automated processing of privacy-relevant information. Automated processing based on well-defined semantics is the baseline for new ways to represent privacy-relevant information, for example by filtering, step-wise refinement or contextualization.
Project(s)
Software Campus
TrUSD