Invisible hand: A privacy preserving mobile crowd sensing framework based on economic models

Liu, B; Zhou, W; Zhu, T; Zhou, H; Lin, X

Invisible hand: A privacy preserving mobile crowd sensing framework based on economic models

Liu, B

Zhou, W

Zhu, T

Zhou, H Lin, X

Permalink

Publisher:: Institute of Electrical and Electronics Engineers
Publication Type:: Journal Article
Citation:: IEEE Transactions on Vehicular Technology, 2017, 66, (5), pp. 4410-4423
Issue Date:: 2017-05-01

Closed Access

	Filename	Description	Size
	Invisible_Hand_A_Privacy_Preserving_Mobile_Crowd_Sensing_Framework_Based_on_Economic_Models.pdf		2.21 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Liu, B https://orcid.org/0000-0002-3603-6617
dc.contributor.author	Zhou, W https://orcid.org/0000-0002-1680-2521
dc.contributor.author	Zhu, T https://orcid.org/0000-0003-3411-7947
dc.contributor.author	Zhou, H
dc.contributor.author	Lin, X
dc.date.accessioned	2022-07-28T03:52:35Z
dc.date.available	2022-07-28T03:52:35Z
dc.date.issued	2017-05-01
dc.identifier.citation	IEEE Transactions on Vehicular Technology, 2017, 66, (5), pp. 4410-4423
dc.identifier.issn	0018-9545
dc.identifier.issn	1939-9359
dc.identifier.uri	http://hdl.handle.net/10453/159287
dc.description.abstract	Privacy issues are strongly impeding the development of mobile crowd sensing (MCS) applications. Under the current MCS framework, processes including bidding, task assignment, and sensed data uploading are all potentially risky for participants. As an effort toward this issue, we propose a framework that enhances the location privacy of MCS applications by reducing the bidding and assignment steps in the MCS cycle. Meanwhile, to reduce the unnecessary privacy loss while maintaining the required quality of service (QoS), economic theory is used to help both the service provider and participants to decide their strategies. We propose schemes based on both the Monopoly and Oligopoly models. In the former case, the participants cooperate to gain exclusive control of the supply of crowd sensing data, while the latter case is a state of limited competition. The parameters in different schemes are analyzed, and the strengths and weaknesses of both schemes are discussed. Additionally, the proposed schemes are evaluated by extensive simulations, and the results are discussed in detail.
dc.language	English
dc.publisher	Institute of Electrical and Electronics Engineers
dc.relation	http://purl.org/au-research/grants/arc/DP140103649
dc.relation.ispartof	IEEE Transactions on Vehicular Technology
dc.relation.isbasedon	10.1109/TVT.2016.2611761
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	08 Information and Computing Sciences, 09 Engineering, 10 Technology
dc.subject.classification	Automobile Design & Engineering
dc.title	Invisible hand: A privacy preserving mobile crowd sensing framework based on economic models
dc.type	Journal Article
utslib.citation.volume	66
utslib.for	08 Information and Computing Sciences
utslib.for	09 Engineering
utslib.for	10 Technology
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
utslib.copyright.status	closed_access	*
pubs.consider-herdc	false
dc.date.updated	2022-07-28T03:52:33Z
pubs.issue	5
pubs.publication-status	Published
pubs.volume	66
utslib.citation.issue	5

Abstract:

Privacy issues are strongly impeding the development of mobile crowd sensing (MCS) applications. Under the current MCS framework, processes including bidding, task assignment, and sensed data uploading are all potentially risky for participants. As an effort toward this issue, we propose a framework that enhances the location privacy of MCS applications by reducing the bidding and assignment steps in the MCS cycle. Meanwhile, to reduce the unnecessary privacy loss while maintaining the required quality of service (QoS), economic theory is used to help both the service provider and participants to decide their strategies. We propose schemes based on both the Monopoly and Oligopoly models. In the former case, the participants cooperate to gain exclusive control of the supply of crowd sensing data, while the latter case is a state of limited competition. The parameters in different schemes are analyzed, and the strengths and weaknesses of both schemes are discussed. Additionally, the proposed schemes are evaluated by extensive simulations, and the results are discussed in detail.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/159287