现有的基于位置隐私保护研究主要提供对用户位置的保护,没有涉及运动方式,例如公交车、步行、驾车等.作为移动对象的重要属性之一,运动方式反映移动特点,对用户行为分析起到了重要的作用.针对包含多种运动方式的移动对象,提出了一种数据隐私保护方法.该方法针对范围查询,包含两种措施:①位置模糊;②查询重设,可有效地将精确运动方式隐藏,避免将真实数据返回给非法查询用户.对两种保护措施进行了分析比较,给出了如何将此方法融合到已有系统中.此外,在位置模糊和查询重设基础上,提出了不同保护粒度的措施使得数据保护度具有可调性以适应不同的应用需求.
The current methods of location-based privacy preserving focus on protecting the location of users, but do not consider transportation modes such as BUS, WALK and CAR. Being one key attribute of moving objects, transportation mode reflects the feature of mobile users and can be used to analyze their behavior. This paper proposes a method including cloaking location and reset modes to preserve transportation modes of moving objects for range queries. Such a technique prevents modes from being disclosed and avoids returning precise data to illegal users. We analyze the two methods and introduce how to integrate the solution into the existing system. In addition, cloaking location and reset modes with different preserving granularity is proposed to have a flexible and tunable method for different applications.