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Location privacy in mobile crowd sensing applications

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posted on 2018-01-01, 00:00 authored by Bo Liu, Wanlei Zhou, Tianqing Zhu, Yong XiangYong Xiang, Kun Wang
The privacy issue strongly impedes 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 which 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, the economic theory is used to help both the service provider (SP) 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.

History

Title of book

Location Privacy in Mobile Applications

Series

SpringerBriefs on Cyber Security Systems and Networks

Chapter number

4

Pagination

47 - 76

Publisher

Springer Nature Singapore

Place of publication

Singapore

ISSN

2522-5561

eISSN

2522-557X

ISBN-13

978-981-13-1704-0

Language

eng

Publication classification

BN Other book chapter, or book chapter not attributed to Deakin

Copyright notice

2018, The Authors

Extent

6

Editor/Contributor(s)

Bo Liu, Wanlei Zhou, Tianqing Zhu, Yong Xiang, Kun Wang

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