Truthful mechanisms for agents that value privacy

Citation:

Yiling Chen, Stephen Chong, Ian A Kash, Tal Moran, and Salil Vadhan. 2013. “Truthful mechanisms for agents that value privacy.” In Proceedings of the fourteenth ACM conference on Electronic commerce, 215-232. Philadelphia, Pennsylvania, USA: ACM. DOI
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Abstract:

Recent work has constructed economic mechanisms that are both truthful and differentially private. In these mechanisms, privacy is treated separately from the truthfulness; it is not incorporated in players' utility functions (and doing so has been shown to lead to non-truthfulness in some cases). In this work, we propose a new, general way of modelling privacy in players' utility functions. Specifically, we only assume that if an outcome o has the property that any report of player i would have led to o with approximately the same probability, then o has small privacy cost to player i. We give three mechanisms that are truthful with respect to our modelling of privacy: for an election between two candidates, for a discrete version of the facility location problem, and for a general social choice problem with discrete utilities (via a VCG-like mechanism). As the number n of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of n).
Acknowledgements: This paper was supported, in part, by Google Inc., Microsoft Research Silicon Valley, and Stanford University.
Last updated on 06/19/2013