Towards a Triad for Data Privacy

Date
2020-01-07
Authors
Covert, Quentin
Steinhagen, Dustin
Francis, Mary
Streff, Kevin
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Data privacy is a topic of interest for researchers, data collection managers, and data system specialists. In an attempt to assuage growing concerns regarding the collection and use of personal data, many organizations have begun developing systems and drafting policies meant to safeguard that data from potential privacy harms. This paper provides a surface-level comparison of data privacy triads from NIST in the United States and ULD in Germany that may form the basis for a future universal definition of data privacy. The analysis shows two different approaches for defining data privacy: one which focuses on the practical implementation of data privacy safeguards (NIST) and one that focuses on defining the highest possible standards to which data processors must be held (ULD).
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Privacy and Economics, data handling, data privacy, data privacy triad, data systems, privacy frameworks
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9 pages
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Proceedings of the 53rd Hawaii International Conference on System Sciences
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Attribution-NonCommercial-NoDerivatives 4.0 International
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