Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

Detail(s)

Original languageEnglish
Title of host publication2018 Annual American Control Conference (ACC)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages998-1002
ISBN (Print)9781538654286
Publication statusPublished - Jun 2018
Externally publishedYes

Publication series

NameProceedings of the American Control Conference
Volume2018-June
ISSN (Print)0743-1619

Conference

Title1st Annual American Control Conference (ACC 2018)
LocationWisconsin Center
PlaceUnited States
CityMilwaukee
Period27 - 29 June 2018

Abstract

In this paper, we consider a multi-sensor estimation problem wherein each sensor collects noisy information about its local process, which is only observed by that sensor, and a common process, which is simultaneously observed by all sensors. The objective is to assess the privacy level of (the local process of) each sensor while the common process is estimated using cloud computing technology. The privacy level of a sensor is defined as the conditional entropy of its local process given the shared information with the cloud. Two information sharing schemes are considered: a local scheme, and a global scheme. Under the local scheme, each sensor estimates the common process based on its measurement and transmits its estimate to a cloud. Under the global scheme, the cloud receives the sum of the sensors' measurements. It is shown that, in the local scheme, the privacy level of each sensor is always above a certain level which is characterized using Shannon's mutual information. It is also proved that this result becomes tight as the number of sensors increases. We also show that the global scheme is asymptotically private, i.e., the privacy loss of the global scheme decreases to zero at the rate of (1/M) where M is the number of sensors.

Citation Format(s)

Privacy of Information Sharing Schemes in a Cloud-based Multi-sensor Estimation Problem. / Nekouei, Ehsan; Skoglund, Mikael; Johansson, Karl H.

2018 Annual American Control Conference (ACC). Institute of Electrical and Electronics Engineers Inc., 2018. p. 998-1002 8431192 (Proceedings of the American Control Conference; Vol. 2018-June).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review