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Geo-Graph-Indistinguishability: Protecting Location Privacy for LBS over Road Networks

机译:地理图不可区分性:通过道路网络为LBS保护位置隐私

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In recent years, Geo-Indistinguishability (GeoI) has been increasingly explored for protecting location privacy in location-based services (LBSs). GeoI is considered a theoretically rigorous location privacy notion since it extends differential privacy to the setting of location privacy. However, GeoI does not consider the road network, which may cause insufficiencies in terms of both privacy and utility for LBSs over a road network. In this paper, we first empirically evaluate the privacy guarantee and the utility loss of GeoI for LBSs over road networks. We identify an extra privacy loss when adversaries have the knowledge of road networks and the degradation of LBS quality of service. Second, we propose a new privacy notion, Geo-Graph-Indistinguishability (GeoGI), for protecting location privacy for LBSs over a road network and design a Graph-Exponential mechanism (GEM) satisfying GeoGI. We also show the relationship between GeoI and GeoGI to explain theoretically why GeoGI is a more suitable privacy notion over road networks. Finally, we evaluate the empirical privacy and utility of the proposed mechanism in real-world road networks. Our experiments confirm that GEM achieves higher utility for LBSs over a road network than the planar Laplace mechanism for Geol under the same empirical privacy level.
机译:近年来,为了保护基于位置的服务(LBS)中的位置隐私,人们越来越多地探索地理不可分辨性(GeoI)。 GeoI从理论上讲是严格的位置隐私概念,因为它将差异隐私扩展到位置隐私设置。但是,GeoI不考虑道路网络,这可能会导致道路网络上LBS的隐私和实用性不足。在本文中,我们首先根据经验评估道路网络上LBS的隐私保证和GeoI的效用损失。当对手了解道路网络和LBS服务质量下降时,我们会发现额外的隐私损失。其次,我们提出了一种新的隐私概念,即地理图形不可区分性(GeoGI),用于保护道路网络上LBS的位置隐私,并设计了一种满足GeoGI的图形指数机制(GEM)。我们还展示了GeoI和GeoGI之间的关系,以从理论上解释为什么GeoGI是道路网络上更合适的隐私概念。最后,我们评估了在现实世界的道路网络中该机制的经验隐私性和实用性。我们的实验证实,在相同的经验隐私级别下,GEM在道路网络上对LBS的使用要比对Geol的平面Laplace机制要高。

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