Privacy-preserving in mobile crowdsensing/ Chuan Zhang, Tong Wu, Youqi Li, Liehuang Zhu.
Zhang, Chuan, author.; Wu, Tong, editor.; Li, Youqi, editor.; Zhu, Liehuang. editor.
2023
QA76.9.A25
Available Online

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Title Privacy-preserving in mobile crowdsensing/ Chuan Zhang, Tong Wu, Youqi Li, Liehuang Zhu.
Author Zhang, Chuan, author.
ISBN 9789811983153 (electronic bk.)
9811983151 (electronic bk.)
9811983143
9789811983146
DOI https://doi.org/10.1007/978-981-19-8315-3
Imprint Singapore : Springer, 2023.
Language English
Description 1 online resource (xvii, 197 pages) : illustrations (black and white).
Other Standard Identifiers 10.1007/978-981-19-8315-3 doi
Call Number QA76.9.A25
Dewey Decimal Classification 005.8
Summary Mobile crowdsensing is a new sensing paradigm that utilizes the intelligence of a crowd of individuals to collect data for mobile purposes by using their portable devices, such as smartphones and wearable devices. Commonly, individuals are incentivized to collect data to fulfill a crowdsensing task released by a data requester. This sensing as a service elaborates our knowledge of the physical world by opening up a new door of data collection and analysis. However, with the expansion of mobile crowdsensing, privacy issues urgently need to be solved. In this book, we discuss the research background and current research process of privacy protection in mobile crowdsensing. In the first chapter, the background, system model, and threat model of mobile crowdsensing are introduced. The second chapter discusses the current techniques to protect user privacy in mobile crowdsensing. Chapter three introduces the privacy-preserving content-based task allocation scheme. Chapter four further introduces the privacy-preserving location-based task scheme. Chapter five presents the scheme of privacy-preserving truth discovery with truth transparency. Chapter six proposes the scheme of privacy-preserving truth discovery with truth hiding. Chapter seven summarizes this monograph and proposes future research directions. In summary, this book introduces the following techniques in mobile crowdsensing: 1) describe a randomizable matrix-based task-matching method to protect task privacy and enable secure content-based task allocation; 2) describe a multi-clouds randomizable matrix-based task-matching method to protect location privacy and enable secure arbitrary range queries; and 3) describe privacy-preserving truth discovery methods to support efficient and secure truth discovery. These techniques are vital to the rapid development of privacy-preserving in mobile crowdsensing.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Wu, Tong, editor.
Li, Youqi, editor.
Zhu, Liehuang. editor.
Available in Other Form Print version: 9789811983146
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Part I. Overview and Basic Concept of Mobile Crowdsensing Technology
Chapter 1. Introduction
Chapter 2. Overview of Mobile Crowdsensing Technology
Part II. Privacy-Preserving Task Allocation
Chapter 3. Privacy-Preserving Content based Task Allocation
Chapter 4. Privacy-Preserving Location based Task Allocation
Part III. Privacy-Preserving Truth Discovery
Chapter 5. Privacy-Preserving Truth Discovery with Truth Transparency
Chapter 6. Privacy-Preserving Truth Discovery with Truth Hiding
Chapter 7. Privacy-Preserving Truth Discovery with Task Hiding
Part IV. Summary and Future Research Directions
Chapter 8. Summary.

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