Application and analysis of multidimensional negative surveys in participatory sensing applications

Michael M. Groat; Benjamin Edwards; James Horey; Wenbo He; Stephanie Forrest

doi:10.1016/j.pmcj.2012.12.004

Application and analysis of multidimensional negative surveys in participatory sensing applications

Michael M. Groat, Benjamin Edwards, James Horey, Wenbo He, Stephanie Forrest

Research output: Contribution to journal › Article › peer-review

15 Scopus citations

Abstract

Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.

Original language	English (US)
Pages (from-to)	372-391
Number of pages	20
Journal	Pervasive and Mobile Computing
Volume	9
Issue number	3
DOIs	https://doi.org/10.1016/j.pmcj.2012.12.004
State	Published - Jun 2013
Externally published	Yes

Keywords

Multidimensional data
Negative surveys
Participatory sensing applications
Privacy

ASJC Scopus subject areas

Software
Information Systems
Hardware and Architecture
Computer Science Applications
Computer Networks and Communications

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10.1016/j.pmcj.2012.12.004

Cite this

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title = "Application and analysis of multidimensional negative surveys in participatory sensing applications",

abstract = "Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.",

keywords = "Multidimensional data, Negative surveys, Participatory sensing applications, Privacy",

author = "Groat, {Michael M.} and Benjamin Edwards and James Horey and Wenbo He and Stephanie Forrest",

note = "Funding Information: The authors thank Esponda, Lane, Rammohan, and Williams for their suggestions, insights, and ideas. MG acknowledges support from Motorola, Inc., Eli Lilly and Company, and NSF grant HRD-0622930 ; WH acknowledges support from DOE NNSA grant DE-FG52-06NA27494 ; SF acknowledges the partial support of NSF (grants CCF-0621900 , CCR-0331580 , SHF-0905236 ), AFOSR MURI grant FA9550-07-1-0532 , and DARPA grant P-1070-113237 .",

year = "2013",

month = jun,

doi = "10.1016/j.pmcj.2012.12.004",

language = "English (US)",

volume = "9",

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journal = "Pervasive and Mobile Computing",

issn = "1574-1192",

publisher = "Elsevier",

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AU - Groat, Michael M.

AU - Edwards, Benjamin

AU - Horey, James

AU - He, Wenbo

AU - Forrest, Stephanie

N1 - Funding Information: The authors thank Esponda, Lane, Rammohan, and Williams for their suggestions, insights, and ideas. MG acknowledges support from Motorola, Inc., Eli Lilly and Company, and NSF grant HRD-0622930 ; WH acknowledges support from DOE NNSA grant DE-FG52-06NA27494 ; SF acknowledges the partial support of NSF (grants CCF-0621900 , CCR-0331580 , SHF-0905236 ), AFOSR MURI grant FA9550-07-1-0532 , and DARPA grant P-1070-113237 .

PY - 2013/6

Y1 - 2013/6

N2 - Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.

AB - Participatory sensing applications rely on individuals to share personal data to produce aggregated models and knowledge. In this setting, privacy concerns can discourage widespread adoption of new applications. We present a privacy-preserving participatory sensing scheme based on negative surveys for both continuous and multivariate categorical data. Without relying on encryption, our algorithms enhance the privacy of sensed data in an energy and computation efficient manner. Simulations and implementation on Android smart phones illustrate how multidimensional data can be aggregated in a useful and privacy-enhancing manner.

KW - Multidimensional data

KW - Negative surveys

KW - Participatory sensing applications

KW - Privacy

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JO - Pervasive and Mobile Computing

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ER -

Application and analysis of multidimensional negative surveys in participatory sensing applications

Abstract

Keywords

ASJC Scopus subject areas

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