Crowdsourcing quality control model protecting location privacy of workers

被引：0
|
作者：
Chu X. [1 ,2 ]
Zhong Q. [2 ]
机构：
[1] Department of Management Science and Engineering, Tsinghua University, Beijing
[2] Faculty of Management and Economics, Dalian University of Technology, Dalian
来源：
| 2016年 / Systems Engineering Society of China卷 / 36期
基金：
中国国家自然科学基金;
关键词：
Crowdsourcing; EM algorithm; Location privacy; Quality control;
D O I：
10.12011/1000-6788(2016)08-2047-09
中图分类号：
学科分类号：
摘要：
Emerging location based crowdsourcing requires workers to submit their own immediate location information to outsourcer along with task labels, for the sake of quality control. However, massive exposed location privacy may incur workers more vulnerable. In order to protect privacy of workers, an approach based on fuzzy space and time is proposed, which can raise uncertainty of information obtained by potential attackers. We theoretically guarantee and experimentally examine that proposed approach does not significantly reduce accuracy of crowdsourcing. The experiment results show: 1) when most workers submit high-quality results, outsourcer can guarantee overall crowdsourcing quality, without worker location information; 2) when error or spammer ratio of workers is high, location information improves quality control ability, nevertheless the fuzzy processing does not weaken the quality. © 2016, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码：2047 / 2055
页数：8
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