Government agencies always need to carefully consider potential risks of
disclosure whenever they publish statistics based on their data or give
external researchers access to the collected data. For this reason, research on
disclosure avoiding techniques has a long tradition at statistical agencies. In
this context, the promise of formal privacy guarantees offered by concepts such
as differential privacy seem to be the panacea enabling the agencies to exactly
quantify and control the privacy loss incurred by any data release. Still,
despite the excitement in academia and industry, most agencies-with the
prominent exception of the U.S. Census Bureau-have been reluctant to even
consider the concept for their data release strategy.

This paper aims to shed some light on potential reasons for this. We argue
that the requirements when implementing differential privacy approaches at
government agencies are often fundamentally different from the requirements in
industry. This raises many challenging problems and open questions that still
need to be addressed before the concept might be used as an overarching
principle when sharing data with the public. The paper will not offer any
solutions to these challenges. Instead, we hope to stimulate some collaborative
research efforts, as we believe that many of the problems can only be addressed
by inter-disciplinary collaborations.

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Author Of this post: <a href="">Joerg Drechsler</a>

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