? 隐私保护的空间众包任务分配
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Journal of Computer Science and Technology 2017, Vol. 32 Issue (5) :905-918    DOI: 10.1007/s11390-017-1772-5
Special Section on Crowdsourced Data Management << Previous Articles | Next Articles >>
隐私保护的空间众包任务分配
An Liu1,2, Member, CCF, Zhi-Xu Li1,*, Member, CCF, Guan-Feng Liu1, Member, CCF, Kai Zheng1,3, Member, CCF, Min Zhang1, Member, CCF, Qing Li4, Senior Member, IEEE Xiangliang Zhang2, Member, IEEE
1 School of Computer Science and Technology, Soochow University, Suzhou 215006, China;
2 King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia;
3 Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing 100872, China;
4 Department of Computer Science, City University of Hong Kong, Hong Kong, China
Privacy-preserving Task Assignment in Spatial Crowdsourcing
An Liu1,2, Member, CCF, Zhi-Xu Li1,*, Member, CCF, Guan-Feng Liu1, Member, CCF, Kai Zheng1,3, Member, CCF, Min Zhang1, Member, CCF, Qing Li4, Senior Member, IEEE Xiangliang Zhang2, Member, IEEE
1 School of Computer Science and Technology, Soochow University, Suzhou 215006, China;
2 King Abdullah University of Science and Technology, Thuwal 23955, Saudi Arabia;
3 Beijing Key Laboratory of Big Data Management and Analysis Methods, Beijing 100872, China;
4 Department of Computer Science, City University of Hong Kong, Hong Kong, China

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摘要 随着移动设备和无线网络的蓬勃发展,空间众包正逐渐成为一种新兴的问题解决方案。通过空间众包,空间任务被分配给一组工人完成。然而为了保证任务分配的有效性,工人和任务请求者都需要将他们的位置暴露给不可信的空间众包系统。本文研究如何在保护工人和任务请求者位置隐私的前提下进行空间众包任务分配。首先基于Paillier加密算法和乱码电路设计了一种安全的任务分配协议。为了提高性能,基于空间层次索引设计了一种安全的近似协议。理论分析了两种协议在半诚实模型下的安全性,并在两个真实的数据集上验证了两种协议的性能。
关键词空间众包   空间任务分配   位置隐私   双向隐私保护     
Abstract: With the progress of mobile devices and wireless networks, spatial crowdsourcing (SC) is emerging as a promising approach for problem solving. In SC, spatial tasks are assigned to and performed by a set of human workers. To enable effective task assignment, however, both workers and task requesters are required to disclose their locations to untrusted SC systems. In this paper, we study the problem of assigning workers to tasks in a way that location privacy for both workers and task requesters are preserved. We first combine Paillier cryptosystem with Yao's garbled circuits to construct a secure protocol that assigns the nearest worker to a task. Considering that this protocol cannot scale to a large number of workers, we then make use of Geohash, a hierarchical spatial index to design a more efficient protocol that can securely find approximate nearest workers. We theoretically show that these two protocols are secure against semi-honest adversaries. Through extensive experiments on two real-world datasets, we demonstrate the efficiency and effectiveness of our protocols.
KeywordsSpatial crowdsourcing   Spatial task assignment   Location privacy   Mutual privacy protection     
Received 2017-03-01;
本文基金:

This work was partially supported by King Abdullah University of Science and Technology (KAUST) and the National Natural Science Foundation of China under Grant Nos. 61572336, 61632016, 61402313, 61572335, and 61472337.

通讯作者: Zhi-Xu Li,zhixuli@suda.edu.cn     Email: zhixuli@suda.edu.cn
About author: An Liu is an associate professor in the School of Computer Science and Technology at Soochow University, Suzhou. He received his Ph.D. degree in computer science from both City University of Hong Kong (CityU), Hong Kong, and University of Science and Technology of China (USTC), Hefei, in 2009. His research interests include spatial databases, crowdsourcing, data security and privacy, and cloud/service computing.
引用本文:   
An Liu, Zhi-Xu Li, Guan-Feng Liu, Kai Zheng, Min Zhang, Qing Li, Xiangliang Zhan.隐私保护的空间众包任务分配[J]  Journal of Computer Science and Technology , 2017,V32(5): 905-918
An Liu, Zhi-Xu Li, Guan-Feng Liu, Kai Zheng, Min Zhang, Qing Li, Xiangliang Zhang.Privacy-preserving Task Assignment in Spatial Crowdsourcing[J]  Journal of Computer Science and Technology, 2017,V32(5): 905-918
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