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
Citation
SHU, Jiangang; LIU, Ximeng; YANG, Kan; ZHANG, Yinghui; JIA, Xiaohua; and DENG, Robert H..
SybMatch: Sybil detection for privacy-preserving task matching in crowdsourcing. (2018). 2018 IEEE Global Communications Conference, GLOBECOM 2018, Abu Dhabi, United Arab Emirates, December 9-13: Proceedings. 1-6.
Available at: https://ink.library.smu.edu.sg/sis_research/4369
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/GLOCOM.2018.8647346