Networked estimation-privacy games

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper studies non-cooperative estimation-privacy games over a network of multiple informed transmitters and one receiver. The transmitters and the receiver have different objectives due to transmitters' privacy concerns which are modeled in the context of the Stackelberg equilibrium of a strategic communication problem. In broad terms, the receiver wants to accurately estimate a random variable, while the transmitters aim to strike the optimal trade-off between providing an accurate measurement and minimizing the amount of leaked information about a private type available to the transmitters. The transmitters, having access to source and type variables, are the leaders and the receiver is the follower. Assuming an entropy based privacy measure on the type variable, a quadratic distortion measure on the source, and jointly Gaussian statistics, we characterize the Stackelberg equilibrium for two different notions of equilibria: I) All transmitters have the identical objective of minimizing the total estimation error subject to an aggregate privacy constraint, ii) Nash equilibria among the transmitters where each one is strategic and aims to minimize its own distortion subject to individual privacy constraints. We show the existence and uniqueness of Nash equilibrium and derive the strategies achieving this unique equilibrium for both notions of equilibrium.

Original languageEnglish (US)
Title of host publication2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages507-510
Number of pages4
ISBN (Electronic)9781509059904
DOIs
StatePublished - Mar 7 2018
Event5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Montreal, Canada
Duration: Nov 14 2017Nov 16 2017

Publication series

Name2017 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017 - Proceedings
Volume2018-January

Other

Other5th IEEE Global Conference on Signal and Information Processing, GlobalSIP 2017
CountryCanada
CityMontreal
Period11/14/1711/16/17

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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