Publication Type
Journal Article
Version
acceptedVersion
Publication Date
8-2018
Abstract
With the development of sharing economy, crowdsourcing as a distributed computing paradigm has become increasingly pervasive. As one of indispensable services for most crowdsourcing applications, task matching has also been extensively explored. However, privacy issues are usually ignored during the task matching and few existing privacy-preserving crowdsourcing mechanisms can simultaneously protect both task privacy and worker privacy. This paper systematically analyzes the privacy leaks and potential threats in the task matching and proposes a single-keyword task matching scheme for the multirequester/multiworker crowdsourcing with efficient worker revocation. The proposed scheme not only protects data confidentiality and identity anonymity against the crowd-server, but also achieves query traceability against dishonest or revoked workers. Detailed privacy analysis and thorough performance evaluation show that the proposed scheme is secure and feasible.
Keywords
Anonymity, crowdsourcing, privacy, revocation, task matching, traceability
Discipline
Information Security
Research Areas
Cybersecurity
Publication
IEEE Internet of Things
Volume
5
Issue
4
First Page
3068
Last Page
3078
ISSN
2327-4662
Identifier
10.1109/JIOT.2018.2830784
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
SHU, Jiangang; LIU, Ximeng; JIA, Xiaohua; YANG, Kan; and DENG, Robert H..
Anonymous privacy-preserving task matching in crowdsourcing. (2018). IEEE Internet of Things. 5, (4), 3068-3078.
Available at: https://ink.library.smu.edu.sg/sis_research/4150
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1109/JIOT.2018.2830784