Title
SybMatch: Sybil Detection for Privacy-Preserving Task Matching in Crowdsourcing
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.
Year
DOI
Venue
2018
10.1109/GLOCOM.2018.8647346
2018 IEEE Global Communications Conference (GLOBECOM)
Keywords
Field
DocType
Sybil detection,crowdsourcing,task matching,privacy-preserving
Computer science,Crowdsourcing,Computer network,Service provider,Revocation,Security analysis
Conference
ISSN
ISBN
Citations 
2334-0983
978-1-5386-4727-1
0
PageRank 
References 
Authors
0.34
0
6
Name
Order
Citations
PageRank
Jiangang Shu168922.01
Ximeng Liu213531.84
Kan Yang376034.29
Yinghui Zhang446828.80
Xiaohua Jia54609303.30
R.H Deng64423362.82