SybMatch: Sybil detection for privacy-preserving task matching in crowdsourcing

SybMatch: Sybil detection for privacy-preserving task matching in crowdsourcing

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 S...

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Bibliographic Details
Main Authors: SHU, Jiangang, LIU, Ximeng, YANG, Kan, ZHANG, Yinghui, JIA, Xiaohua, DENG, Robert H.
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2018
Subjects:
Crowdsourcing
Privacy-preserving
Sybil detection
Task matching
Information Security
Online Access:https://ink.library.smu.edu.sg/sis_research/4369
https://ink.library.smu.edu.sg/context/sis_research/article/5372/viewcontent/SybMatch_shu_2018_afv.pdf
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Institution: Singapore Management University
Language: English
Description
Summary: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.

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