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The authors describe a new paradigm for articulating need-to-protect and need-to-share policies that shows promise for enabling automated derivation of the downgrading rule-sets needed to comply with these policies in systems that share data. This new paradigm is based on fine-grained semantic policy specifications in terms of context, content, Purpose, and Anti-purpose that are expressed in a machine-understandable language. Their approach is based on an existing reasoning capability that can handle simple downgrading cases. Extensions to handle more complex cases are discussed. Although not yet a complete, turnkey solution to the overall data sharing and privacy problem, they posit that their approach provides an auspicious research vector for future work towards achieving that goal.
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