基于博弈分析的众包交通监测隐私保护机制

Enhancing Privacy Preserving for Crowdsourced Monitoring——A Game Theoretic Analysis Based Approach

众包交通监测利用移动终端上传的GPS位置信息实时感知交通状况,具有广阔的应用前景。然而,上传的GPS信息会泄露用户隐私。该文基于博弈论分析用户上传行为,提出隐私保护的优化上传机制。首先建立用户上传行为与路况服务质量和隐私泄露之间的关系,据此构建不完全信息博弈模型,以便分析用户上传行为;然后,根据用户上传博弈纳什均衡,提出用户终端可控的隐私保护优化上传机制。理论分析表明,该文提出的上传机制最大化用户效用,具有激励相容特性;通过真实数据实验验证,上传机制能够提高用户的隐私保护度,以及算法的激励相容特性。

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.