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A location privacy preserving algorithm for mobile LBS

机译:移动LBS的位置隐私保护算法

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Location-Based Service (LBS) combined with mobile devices and Internet become more and more popular, and are widely used in traffic navigation, intelligent logistics and the point of interest query. However, most users worry about their privacy when using the LBS because they should provide their accurate location and query content to the untrustworthy server. Therefore, how to protect users' privacy is very important to the mobile LBS application. Continuous queries tracking attack is one of the typical attack models in mobile LBS. This paper analyzes the query association attack model for the continuous query in mobile LBS, formalizes the background knowledge of attackers considering the spatiotemporal dimension. In order to resist the query association attack for continuous query in mobile LBS, this paper improves the k-sharing model and proposes the location distribution aware cloaking algorithm which is distribution-aware when generating cloak regions, it satisfies the m-invariant and l-diversity. Finally, a set of experiments show the effectiveness of the approach.
机译:结合移动设备和Internet的基于位置的服务(LBS)变得越来越流行,并且广泛用于交通导航,智能物流和兴趣点查询。但是,大多数用户在使用LBS时都会担心自己的隐私,因为他们应向不可靠的服务器提供准确的位置并查询内容。因此,如何保护用户的隐私对移动LBS应用非常重要。连续查询跟踪攻击是移动LBS中的典型攻击模型之一。本文分析了移动LBS中连续查询的查询关联攻击模型,并根据时空维度对攻击者的背景知识进行了形式化。为了抵抗移动LBS中连续查询的查询关联攻击,本文对k共享模型进行了改进,提出了在生成隐身区域时能够感知分布的位置分布感知隐身算法,该算法满足m不变和l-多样性。最后,一组实验证明了该方法的有效性。

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