Download PDFOpen PDF in browserLogic, Probability, and Privacy: A Framework for Specifying Privacy Requirements11 pages•Published: June 22, 2012AbstractIn this paper, we propose a probabilistic hybrid logic for the specification of data privacy requirements. The proposed logic is a combination of quantitative uncertainty logic and basic hybrid logic with a satisfaction operator. We show that it is expressive enough for the specification of many well-known data privacy requirements, such as <math>k</math>-anonymity, <math>l</math>-diversity and its precursor logical safety, <math>t</math>-closeness, and <math>δ</math>-disclosure privacy. The main contribution of the work is twofold. On one hand, the logic provides a common ground to express and compare existing privacy criteria. On the other hand, the uniform framework can meet the specification needs of combining new criteria as well as existing ones.Keyphrases: data privacy, hybrid logic, information systems, probabilistic logic In: Andrei Voronkov (editor). Turing-100. The Alan Turing Centenary, vol 10, pages 157-167.
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