Local Differential Privacy For Evolving Data

Authors:
Matthew Joseph University of Pennsylvania
Aaron Roth University of Pennsylvania
Jonathan Ullman Northeastern University
Bo Waggoner Microsoft

Introduction:

There are now several large scale deployments of differential privacy used to collect statistical information about users.

Abstract:

There are now several large scale deployments of differential privacy used to collect statistical information about users. However, these deployments periodically recollect the data and recompute the statistics using algorithms designed for a single use. As a result, these systems do not provide meaningful privacy guarantees over long time scales. Moreover, existing techniques to mitigate this effect do not apply in the ``local model'' of differential privacy that these systems use.

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