Epsilon Voting: Mechanism Design for Parameter Selection in Differential Privacy

Kohli, Nitin, and Paul Laskowski. "Epsilon Voting: Mechanism Design for Parameter Selection in Differential Privacy." In 2018 IEEE Symposium on Privacy-Aware Computing (PAC), pp. 19-30. IEEE, 2018.


The behavior of a differentially private system is governed by a parameter epsilon which sets a balance between protecting the privacy of individuals and returning accurate results. While a system owner may use a number of heuristics to select epsilon, existing techniques may be unresponsive to the needs of the users who's data is at risk. A promising alternative is to allow users to express their preferences for epsilon. In a system we call epsilon voting, users report the parameter values they want to a chooser mechanism, which aggregates them into a single value. We apply techniques from mechanism design to ask whether such a chooser mechanism can itself be truthful, private, anonymous, and also responsive to users. Without imposing restrictions on user preferences, the only feasible mechanisms belong to a class we call randomized dictatorships with phantoms. This is a restrictive class in which at most one user has any effect on the chosen epsilon. On the other hand, when users exhibit single-peaked preferences, a broader class of mechanisms - ones that generalize the median and other order statistics - becomes possible.

Research Area(s)

Last updated:

November 7, 2018