English

Truthful Mechanisms for Agents that Value Privacy

Computer Science and Game Theory 2012-11-14 v2

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 oo has the property that any report of player ii would have led to oo with approximately the same probability, then oo has small privacy cost to player ii. 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 nn of players increases, the social welfare achieved by our mechanisms approaches optimal (as a fraction of nn).

Keywords

Cite

@article{arxiv.1111.5472,
  title  = {Truthful Mechanisms for Agents that Value Privacy},
  author = {Yiling Chen and Stephen Chong and Ian A. Kash and Tal Moran and Salil Vadhan},
  journal= {arXiv preprint arXiv:1111.5472},
  year   = {2012}
}
R2 v1 2026-06-21T19:40:25.449Z