Enhancing Privacy Preserving for Crowdsourced Monitoring A Game Theoretic Analysis Based Approach
HE Yunhua①② SUN Limin①② YANG Weidong② LI Hong②
①(School of Computer Science, Xidian University, Xi’an 710071, China) ②(Beijing Key Laboratory of Internet of Things Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China)
Crowdsourcing traffic monitoring is a promising application, which exploits ubiquitous mobile devices to upload GPS samples to obtain live road traffic. However, uploading the sensitive location information raises significant privacy issues. By analyzing the upload behavior of mobile users, this paper designs a privacy preserving traffic data collection mechanism. Using the relationships among the traffic service quality, privacy loss and the upload behavior, an incomplete information game is built to analyze the upload behavior of users. Based on the existence and uniqueness of Nash equilibrium in this game, a user-centric privacy preserving traffic data collection mechanism is proposed, which can maximize the utilities of users, and this mechanism has a feature of incentive compatible. Finally, the experimental results on real world traffic data confirm the effectiveness of privacy protecting and the feature of incentive compatible.
何云华,孙利民,杨卫东,李红. 基于博弈分析的众包交通监测隐私保护机制[J]. 电子与信息学报, 2016, 38(2): 340-346.
HE Yunhua, SUN Limin, YANG Weidong, LI Hong. Enhancing Privacy Preserving for Crowdsourced Monitoring A Game Theoretic Analysis Based Approach. JEIT, 2016, 38(2): 340-346.
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