On the data quality in privacy-preserving mobile crowdsensing systems with untruthful reporting
File(s)
Accepted version
Author(s)
Zhao, Cong
Yang, Shusen
McCann, Julie Ann
Type
Journal Article
Abstract
The proliferation of mobile smart devices with ever improving sensing capacities means that human-centric Mobile Crowdsensing Systems (MCSs) can economically provide a large scale and flexible sensing solution. The use of personal mobile devices is a sensitive issue, therefore it is mandatory for practical MCSs to preserve private information (the user's true identity, precise location, etc.) while collecting the required sensing data. However, well intentioned privacy protection techniques also conceal autonomous, or even malicious, behaviors of device owners (termed as self-interested), where the objectivity and accuracy of crowdsensing data can therefore be severely threatened. The issue of data quality due to untruthful reporting in privacy-preserving MCSs has been yet to produce solutions. Bringing together game theory, algorithmic mechanism design, and truth discovery, we develop a mechanism to guarantee and enhance the quality of crowdsensing data without jeopardizing the privacy of MCS participants. Together with solid theoretical justifications, we evaluate the performance of our proposal with extensive real-world MCS trace-driven simulations. Experimental results demonstrate the effectiveness of our mechanism on both enhancing the quality of the crowdsensing data and eliminating the motivation of MCS participants, even when their privacy is well protected, to report untruthfully.
Date Issued
2021-02-01
Date Acceptance
2019-09-01
Citation
IEEE Transactions on Mobile Computing, 2021, 20 (2), pp.647-661
ISSN
1536-1233
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Start Page
647
End Page
661
Journal / Book Title
IEEE Transactions on Mobile Computing
Volume
20
Issue
2
Copyright Statement
© 2019 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.
Sponsor
The Alan Turing Institute
Identifier
https://ieeexplore.ieee.org/document/8847467
Grant Number
ATIPO000003394
Subjects
Science & Technology
Technology
Computer Science, Information Systems
Telecommunications
Computer Science
Mobile crowdsensing systems
privacy preservation
data quality
untruthful reporting
Networking & Telecommunications
0805 Distributed Computing
0906 Electrical and Electronic Engineering
1005 Communications Technologies
Publication Status
Published
Date Publish Online
2019-09-24