SybMatch: Sybil Detection for Privacy-Preserving Task Matching in Crowdsourcing

Authors

Jiangang Shu, City University of Hong Kong
Ximeng Liu, Singapore Management University
Kan Yang, University of MemphisFollow
Yinghui Zhang, Xi'an Institute of Posts and TelecommunicationsFollow
Xiaohua Jia, City University of Hong Kong
Robert H. Deng, Singapore Management University

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.

Publication Title

2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings

Recommended Citation

Shu, J., Liu, X., Yang, K., Zhang, Y., Jia, X., & Deng, R. (2018). SybMatch: Sybil Detection for Privacy-Preserving Task Matching in Crowdsourcing. 2018 IEEE Global Communications Conference, GLOBECOM 2018 - Proceedings https://doi.org/10.1109/GLOCOM.2018.8647346