PriSTE: Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services
PriSTE: Protecting Spatiotemporal Event Privacy in Continuous Location-Based Services
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DOI：
10.14778/3352063.3352086
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发表时间：
2019-08
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影响因子：
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通讯作者：
Yang Cao;Yonghui Xiao;Li Xiong;Liquan Bai;Masatoshi Yoshikawa
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作者：
Yang Cao;Yonghui Xiao;Li Xiong;Liquan Bai;Masatoshi Yoshikawa
位置隐私保护机制（LPPM）已被广泛研究，以保护用户的位置在基于位置的服务。然而，当用户的扰动位置被连续发布时，现有的LPPM可能无法保护用户的敏感时空事件，例如“上周去过医院”或“每天早上和下午定期在位置1和位置2之间通勤”（很容易推断位置1和2可能是家和办公室）。在这个演示中，我们展示了PriSTE在连续位置发布中保护时空事件隐私。首先，为了提高用户对这样一个新的隐私目标的认识，我们设计了一个交互式工具来演示如何准确的对手可以推断出一个秘密的时空事件的位置序列，甚至LPPM保护的位置。与会者可以发现，一些时空事件是相当危险的，即使这些最先进的LPPM并不总是保护时空事件的隐私。其次，我们演示了用户如何使用PriSTE自动或手动转换LPPM的位置隐私到一个连续的基于位置的服务中保护时空事件隐私。最后，我们可视化的隐私和效用之间的权衡，使用户可以选择适当的隐私参数在不同的应用场景。
Location privacy-preserving mechanisms (LPPMs) have been extensively studied for protecting a user’s location in location-based services. However, when user’s perturbed locations are released continuously, existing LPPMs may not protect users’ sensitive spatiotemporal event , such as “visited hospital in the last week” or “regularly commuting between location 1 and location 2 every morning and afternoon” (it is easy to infer that locations 1 and 2 may be home and office). In this demonstration, we demonstrate PriSTE for protecting spatiotemporal event privacy in continuous location release. First, to raise users’ awareness of such a new privacy goal, we design an interactive tool to demonstrate how accurate an adversary could infer a secret spatiotemporal event from a sequence of locations or even LPPM-protected locations. The attendees can find that some spatiotemporal events are quite risky and even these state-of-the-art LPPMs do not always protect spatiotemporal event privacy. Second, we demonstrate how a user can use PriSTE to automatically or manually convert an LPPM for location privacy into one protecting spatiotemporal event privacy in continuous location-based services. Finally, we visualize the trade-off between privacy and utility so that users can choose appropriate privacy parameters in different application scenarios.