Protecting location privacy using location semantics
Protecting location privacy using location semantics
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DOI：
10.1145/2020408.2020602
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发表时间：
2011-08
期刊：
影响因子：
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通讯作者：
Byoungyoung Lee;Jinoh Oh;Hwanjo Yu;Jong Kim
中科院分区：
文献类型：
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作者：
Byoungyoung Lee;Jinoh Oh;Hwanjo Yu;Jong Kim
随着移动设备的使用增加，基于位置的服务（LBS）变得越来越流行，因为它提供了更方便的上下文感知服务。然而，由于服务的性质，LBS 引入了位置隐私问题。基于k-匿名和l-多样性的位置隐私保护方法已经被提出来提供LBS的匿名使用。然而，k-匿名和l-多样性方法仍然会危及用户的隐私，因为在使用LBS时位置语义信息很容易被泄露。本文提出了一种新颖的位置隐私保护技术，可以保护位置语义免受对手的攻击。在我们的方案中，位置语义首先从位置数据中学习。然后，可信匿名服务器通过用语义异构位置进行伪装来使用位置语义信息来执行匿名化。因此，位置语义信息保持安全，因为隐藏是通过语义异构位置完成的，并且真实位置信息不会传递到 LBS 应用程序。本文提出了学习位置语义并实现语义安全伪装的算法。
As the use of mobile devices increases, a location-based service (LBS) becomes increasingly popular because it provides more convenient context-aware services. However, LBS introduces problematic issues for location privacy due to the nature of the service. Location privacy protection methods based on k-anonymity and l-diversity have been proposed to provide anonymized use of LBS. However, the k-anonymity and l-diversity methods still can endanger the user's privacy because location semantic information could easily be breached while using LBS. This paper presents a novel location privacy protection technique, which protects the location semantics from an adversary. In our scheme, location semantics are first learned from location data. Then, the trusted-anonymization server performs the anonymization using the location semantic information by cloaking with semantically heterogeneous locations. Thus, the location semantic information is kept secure as the cloaking is done with semantically heterogeneous locations and the true location information is not delivered to the LBS applications. This paper proposes algorithms for learning location semantics and achieving semantically secure cloaking.