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

• 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
• Institution: Singapore Management University

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.