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We present a secure design for a map-reduce framework that guarantees preservation of privacy of the original data. We use Hadoop as a typical environment for illustration. That is, in spite of the data divisions/replications for the computations, the privacy of the original data remains invariant. Specifically, we use the novel information flow model called RWFM model that assures that in spite of...
Privacy policies are often defined in terms of purposes for which the information may be used. Recent work on specification and enforcement of purpose-based privacy policies proceeds by expressing purpose constraints using modal logics for defining when a sequence of actions is "only for" and "not for" a purpose, where a purpose is modelled using either Marko decision processes...
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