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A Hilbert-based framework for preserving privacy in location-based services

机译:基于希尔伯特的框架,用于在基于位置的服务中保护隐私

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摘要

Preserving user's privacy has recently drawn special attention in the field of location-based services and many techniques such as k-anonymity or obfuscation have been suggested to protect user's privacy. All of these traditional techniques are, however, geometry-based and separated from the database level. This separation causes the query processing to involve in two phases, querying the database to retrieve the exact locations of users and then modifying them to decrease the quality of this information. This two-phase process is time-consuming due to the number of disk accesses required to retrieve the user's exact location. Also, these geometry-based techniques cannot guarantee location privacy when the adversary gains knowledge about the geography of the obfuscated region. We address these problems by proposing Hilbert-based framework for preserving user's privacy and B~(ob)-tree for supporting geographic-aware obfuscation. Experiments and analyses show that this framework provides a significant improvement over the algorithm separated from the database level for both query processing time and location privacy protection.
机译:近年来,在基于位置的服务领域中,保护用户的隐私受到了特别的关注,并且已经提出了许多诸如k-匿名或混淆的技术来保护用户的隐私。但是,所有这些传统技术都是基于几何的,并且与数据库级别分开。这种分离导致查询处理涉及两个阶段,即查询数据库以检索用户的确切位置,然后对其进行修改以降低此信息的质量。由于需要检索用户确切位置的磁盘访问次数,因此此两阶段过程非常耗时。同样,当对手获得有关模糊区域地理的知识时,这些基于几何的技术也无法保证位置的隐私。我们通过提出基于Hilbert的框架来保护用户的隐私和B〜(ob)树来支持地理感知混淆来解决这些问题。实验和分析表明,该框架相对于从数据库级别分离的算法在查询处理时间和位置隐私保护方面均提供了显着改进。

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