NDLI: Universally optimal privacy mechanisms for minimax agents

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Universally optimal privacy mechanisms for minimax agents

Content Provider	ACM Digital Library
Author	Sundararajan, Mukund Gupte, Mangesh
Abstract	A scheme that publishes aggregate information about sensitive data must resolve the trade-off between utility to information consumers and privacy of the database participants. Differential privacy [5] is a well-established definition of privacy--this is a universal guarantee against all attackers, whatever their side-information or intent. Can we have a similar universal guarantee for utility? There are two standard models of utility considered in decision theory: Bayesian and minimax [13]. Ghosh et. al. [8] show that a certain "geometric mechanism" gives optimal utility to all Bayesian information consumers. In this paper, we prove a similar result for minimax information consumers. Our result also works for a wider class of information consumers which includes Bayesian information consumers and subsumes the result from [8]. We model information consumers as minimax (risk-averse) agents, each endowed with a loss-function which models their tolerance to inaccuracies and each possessing some side-information about the query. Further, information consumers are rational in the sense that they actively combine information from the mechanism with their side-information in a way that minimizes their loss. Under this assumption of rational behavior, we show that for every fixed count query, the geometric mechanism is universally optimal for all minimax information consumers. Additionally, our solution makes it possible to release query results, when information consumers are at different levels of privacy, in a collusion-resistant manner.
Starting Page	135
Ending Page	146
Page Count	12
File Format	PDF
ISBN	9781450300339
DOI	10.1145/1807085.1807105
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-06-06
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Differential privacy Minimax Decision theory Linear algebra Universally optimal privacy
Content Type	Text
Resource Type	Article

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