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Full-Text Articles in Physical Sciences and Mathematics
Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng
Sybmatch: Sybil Detection For Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Kan Yang, Yinghui Zhang, Xiaohua Jia, Robert H. Deng
Research Collection School Of Computing and Information Systems
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.
Anonymous Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Xiaohua Jia, Kan Yang, Robert H. Deng
Anonymous Privacy-Preserving Task Matching In Crowdsourcing, Jiangang Shu, Ximeng Liu, Xiaohua Jia, Kan Yang, Robert H. Deng
Research Collection School Of Computing and Information Systems
With the development of sharing economy, crowdsourcing as a distributed computing paradigm has become increasingly pervasive. As one of indispensable services for most crowdsourcing applications, task matching has also been extensively explored. However, privacy issues are usually ignored during the task matching and few existing privacy-preserving crowdsourcing mechanisms can simultaneously protect both task privacy and worker privacy. This paper systematically analyzes the privacy leaks and potential threats in the task matching and proposes a single-keyword task matching scheme for the multirequester/multiworker crowdsourcing with efficient worker revocation. The proposed scheme not only protects data confidentiality and identity anonymity against the crowd-server, …
A Data-Driven Analysis Of Workers' Earnings On Amazon Mechanical Turk, Kotaro Hara, Abigail Adams, Kristy Milland, Saiph Savage, Chris Callison-Burch, Jeffrey P. Bigham
A Data-Driven Analysis Of Workers' Earnings On Amazon Mechanical Turk, Kotaro Hara, Abigail Adams, Kristy Milland, Saiph Savage, Chris Callison-Burch, Jeffrey P. Bigham
Research Collection School Of Computing and Information Systems
A growing number of people are working as part of on-line crowd work. Crowd work is often thought to be low wage work. However, we know little about the wage distribution in practice and what causes low/high earnings in this setting. We recorded 2,676 workers performing 3.8 million tasks on Amazon Mechanical Turk. Our task-level analysis revealed that workers earned a median hourly wage of only ~$2/h, and only 4% earned more than $7.25/h. While the average requester pays more than $11/h, lower-paying requesters post much more work. Our wage calculations are influenced by how unpaid work is accounted for, …
Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou
Slade: A Smart Large-Scale Task Decomposer In Crowdsourcing, Yongxin Tong, Lei Chen, Zimu Zhou, H. V. Jagadish, Lidan Shou
Research Collection School Of Computing and Information Systems
Crowdsourcing has been shown to be effective in a wide range of applications, and is seeing increasing use. A large-scale crowdsourcing task often consists of thousands or millions of atomic tasks, each of which is usually a simple task such as binary choice or simple voting. To distribute a large-scale crowdsourcing task to limited crowd workers, a common practice is to pack a set of atomic tasks into a task bin and send to a crowd worker in a batch. It is challenging to decompose a large-scale crowdsourcing task and execute batches of atomic tasks, which ensures reliable answers at …