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Truthful Mechanisms for Agents that Value Privacy

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2013

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ACM Press
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Chen, Yiling, 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 - EC ’13, 215-232. New York: ACM Press.

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).

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Theory, Economics, Mechanism design, privacy, differential privacy

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