Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

12-2018

Abstract

The past decade has witnessed the rise of crowdsourcing, and privacy in crowdsourcing has also gained rising concern in the meantime. In this paper, we focus on the privacy leaks and sybil attacks during the task matching, and propose a privacy-preserving task matching scheme, called SybMatch. The SybMatch scheme can simultaneously protect the privacy of publishers and subscribers against semi-honest crowdsourcing service provider, and meanwhile support the sybil detection against greedy subscribers and efficient user revocation. Detailed security analysis and thorough performance evaluation show that the SybMatch scheme is secure and efficient.

Keywords

Crowdsourcing, Privacy-preserving, Sybil detection, Task matching

Discipline

Information Security

Research Areas

Cybersecurity

Publication

2018 IEEE Global Communications Conference, GLOBECOM 2018, Abu Dhabi, United Arab Emirates, December 9-13: Proceedings

First Page

1

Last Page

6

ISBN

9781538647271

Identifier

10.1109/GLOCOM.2018.8647346

Publisher

IEEE

City or Country

Piscataway, NJ

Additional URL

https://doi.org/10.1109/GLOCOM.2018.8647346

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