移动定位社交服务下的位置隐私保护方法

Location privacy protection in location-based social networking services

为了在保障移动社交网络服务质量的前提下不泄露用户的位置隐私,该文基于K-匿名模型提出一种增强的K-匿名位置隐私保护模型。它从时间和空间两个角度出发,寻找与目标地理信息最接近的其他"K-1"条地理位置信息,通过泛化降低信息粒度,从而使它们在时间和空间上彼此无法区分,实现保护用户位置隐私的目的。同时,该模型也提出针对位置历史记录匿名的构建算法,用于离线场景下位置历史记录的匿名保护。实验显示该方法在构建匿名子集上效率和质量都很高。

In order to protect the user＇s location privacy without compromising the quality of the mobile social networking service, this paper proposes an enhanced K-anonymous location privacy protection model based on a K-anonymous model. In order to achieve the goal of the user location privacy protection, the model looks for other ＂K-1 ＂location information which is the closest to the target location information from the perspective of time and space, reducing information granularity by generalization. All the location information can not be distinguished from each other. Location history anonymity algorithm is put forward for the anonymity protection of location history. Experiments show that this method has higher efficiency on constructing an anonymous subset.