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The Location Privacy Preserving Scheme Based on Hilbert Curve for Indoor LBS

机译:基于Hilbert曲线的室内LBS的位置隐私保留方案

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Location-based service (LBS) brings great benefits to individuals and society, but it also exist serious threat to users' privacy, because LBS supplier may leak users' location-related information. It is important to protect users' privacy while providing LBS. However, current privacy protection and location recommendation service have the problem of timeliness. To address the problem, a location privacy preserving scheme based on Hilbert curve for LBS is proposed. Firstly, a Hilbert curve is generated from given parameters for coordinate transformation to correspond to Hilbert coordinates. Secondly, the points of users are transmitted to the location service provider (LSP) through the randomly generated point of the fog server without using such methods as K anonymous, which satisfy the demand. Then the user's point of interest (POI) could be obtained by the weighted KNN algorithm of LSP. Finally, the user's POI would be transmitted back to the client. Simulation results show that the proposed scheme provide location privacy with timeliness.
机译:基于位置的服务(LBS)对个人和社会带来了很大的好处,但它也存在对用户隐私的严重威胁,因为LBS供应商可能会泄漏用户的位置相关信息。在提供LBS的同时保护用户隐私非常重要。但是,目前的隐私保护和位置推荐服务具有及时性问题。为了解决问题,提出了一种基于洛伯特曲线的LBS的位置隐私保留方案。首先,从给定参数产生Hilbert曲线,用于坐标变换以对应于Hilbert坐标。其次,用户通过雾服务器的随机生成的点传输到位置服务提供商(LSP),而不使用这种方法作为满足需求的k匿名。然后,用户的兴趣点(POI)可以通过LSP的加权KNN算法获得。最后,用户的POI将被发送回客户端。仿真结果表明,该方案提供了及时性隐私。

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