基于虚拟位置隐私保护的车载云地理围栏服务框架

Hani Al-Balasmeh, Maninder P. Singh, Raman Singh
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引用次数: 1

摘要

随着各种移动应用程序的日益普及,许多应用程序要求用户在其设备上启用位置服务。例如,地理防御服务可以定义为建立虚拟地理边界。启用此服务将触发进入和退出边界区域,并通知用户和受信任的第三方。使用地理围栏最重要的问题是不同应用程序之间共享位置坐标的隐私性。在本文中,提出了一个名为“TIET-GEO”的框架,允许用户定义地理围栏边界;此外,当全球定位系统(GPS)设备进入/退出特定区域时,它会实时监控这些设备。该框架还提出了一个虚拟隐私保护算法,当用户从基于位置的服务(LBS)请求兴趣点(POI)时,在真实轨迹周围生成k个虚拟位置。本文旨在增强地理围栏服务中的位置隐私保护,基于地理围栏区域的半径大小,在用户位置周围生成k-dummy位置。该框架通过在客户端和服务之间生成秘密的令牌密钥认证,使用令牌密钥认证对VCN服务中的用户进行授权。所获得的结果表明,所提出框架的有效性取决于来自不同来源(如智能物联网设备和数据集)响应的灵活性和可靠性等参数。
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Framework of Geofence Service using Dummy Location Privacy Preservation in Vehicular Cloud Network
With the increasing prevalence of different mobile apps, many applications require users to enable the location service on their devices. For example, the geofence service can be defined as establishing virtual geographical boundaries. Enabling this service triggers entering and exiting the boundary area and notifies the users and trusted third parties. The foremost concern of using geofence is the privacy of location coordinates shared among different applications. In this paper, a framework called ‘TIET-GEO’ is proposed that allows users to define the geofence boundary; in addition, it monitors Global Positioning System (GPS) devices in real-time when they enter/exit a specific area. The proposed framework also proposes a dummy privacy preservation algorithm to generate K-dummy locations around the real trajectories when the user requests the Point Of Interest (POI) from the Location-Based Services (LBS). This article aims to enhance the location privacy preservation in geofence service, by generating a k-dummy location around the user location based on the radius size of the geofence area. The proposed framework uses token keys authentication to authorize the users in the Vehicular Cloud Network (VCN) service by generating secret token keys authentication between the client and services. The results obtained show the effectiveness of the proposed framework was on parameters like flexibility and reliability of responses from different sources, such as smart IoT devices and datasets.
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