Is privacy compatible with truthfulness?
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
Bayesian mechanism design with efficiency, privacy, and approximate truthfulness
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Take it or leave it: running a survey when privacy comes at a cost
WINE'12 Proceedings of the 8th international conference on Internet and Network Economics
Truthful mechanisms for agents that value privacy
Proceedings of the fourteenth ACM conference on Electronic commerce
ACM SIGecom Exchanges
Mechanism design in large games: incentives and privacy
Proceedings of the 5th conference on Innovations in theoretical computer science
Redrawing the boundaries on purchasing data from privacy-sensitive individuals
Proceedings of the 5th conference on Innovations in theoretical computer science
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In this paper we show that for any mechanism design problem with the objective of maximizing social welfare, the exponential mechanism can be implemented as a truthful mechanism while still preserving differential privacy. Our instantiation of the exponential mechanism can be interpreted as a generalization of the VCG mechanism in the sense that the VCG mechanism is the extreme case when the privacy parameter goes to infinity. To our knowledge, this is the first general tool for designing mechanisms that are both truthful and differentially private.