一种满足共匿性要求的空间K-匿名及分割算法

Reciprocal_cloaking and Partition Algorithms for Spatial K-Anonymity

空间K-匿名(spatial K-anonymity,SKA)是利用K-匿名的概念来保护用户免受基于位置的攻击.然而,现有的满足共匿性(reciprocity)要求的算法—Hilbert隐匿依赖特定的数据结构,而所提出的共匿算法在采用用户—匿名器—LBS架构的情况下能够使用现有的空间索引.在此基础上,进一步提出了一种新型调节中值分割方法,以提高有效性(即最小化匿名空间区域的尺寸)和查询效率(构建代价).最后,实验证明所提出的方法具有更优良的性能,并且由于使用通用的空间索引,所以该方法也支持传统的空间查询.

Spatial K-anonymity （ SKA ） exploits the concept of K-anonymity in order to protect the identity of users from locationbased attacks. However, the existing reciprocal method （Hilbert Cloak ） relies on a specialized data structure. In contrast, the proposed reciprocal algorithm uses existing spatial indices on the user locations based on the framework of User-Anonymizer-LBS. At the same time, an adjusted median splits algorithm is provided, aimed on effectiveness （ i.e., minimum anonymizing spatial region size） and efficiency （i. e. , construction cost}. Finally, the experimental results verify that the proposed methods have higher performance. Moreover, since employing general-purpose spatial indices, the proposed methods support conventional spatial queries as well.