Take it or leave it: Running a survey when privacy comes at a cost

Katrina Ligett*, Aaron Roth

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

45 Scopus citations


In this paper, we consider the problem of estimating a potentially sensitive (individually stigmatizing) statistic on a population. In our model, individuals are concerned about their privacy, and experience some cost as a function of their privacy loss. Nevertheless, they would be willing to participate in the survey if they were compensated for their privacy cost. These cost functions are not publicly known, however, nor do we make Bayesian assumptions about their form or distribution. Individuals are rational and will misreport their costs for privacy if doing so is in their best interest. Ghosh and Roth recently showed in this setting, when costs for privacy loss may be correlated with private types, if individuals value differential privacy, no individually rational direct revelation mechanism can compute any non-trivial estimate of the population statistic. In this paper, we circumvent this impossibility result by proposing a modified notion of how individuals experience cost as a function of their privacy loss, and by giving a mechanism which does not operate by direct revelation. Instead, our mechanism has the ability to randomly approach individuals from a population and offer them a take-it-or-leave-it offer. This is intended to model the abilities of a surveyor who may stand on a street corner and approach passers-by.

Original languageAmerican English
Title of host publicationInternet and Network Economics - 8th International Workshop, WINE 2012, Proceedings
Number of pages14
StatePublished - 2012
Externally publishedYes
Event8th International Workshop on Internet and Network Economics, WINE 2012 - Liverpool, United Kingdom
Duration: 10 Dec 201212 Dec 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7695 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference8th International Workshop on Internet and Network Economics, WINE 2012
Country/TerritoryUnited Kingdom


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