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)

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/JIOT.2018.2830784

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