基于Geohash编码的位置隐私保护算法

针对基于位置服务中用户位置信息易泄露用户个人隐私的问题,利用Geohash编码优化网格化Casper模型,提出了基于Geohash的位置隐私保护算法G-Casper。该算法采用自底向上的机制,对目标位置的Geohash编码进行字符串模糊查询来确定组成匿名区域的k-1个近邻,在扩大扫描区域时,对请求用户所在网格以及周边网格跨域扫描,然后再进行层级的递归,同时使用Lmax和Lmin两个参数来控制匿名区域范围,最终通过剪枝算法删除冗余网格并随机发送一个候选网格区域代替用户原本位置,达到k-匿名的效果。实验结果表明,该算法能够更好地提高位置服务的质量和匿名区域的成功率,并且减少了查询时间和所需储存空间。

Location Privacy Protection Algorithm Based on Geohash Encoding

Aiming at the problem that users’ location information is easily leaked in location-based services, this paper uses Geohash coding to optimize the gridding Casper model, and proposes a Geohash based location preserving-privacy algorithm G-Casper. The algorithm uses a bottom-up mechanism of Geohash encoding the target location to determine the composition of the anonymous region k-1] neighbor string fuzzy query. In expanding the scanning area,  the requested user is in the grid and the surrounding grid by crossing area scanning, and then the level recursion , using Lmax] and Lmin]control anonymous area. Finally, used by the pruning algorithm to remove redundant grid, a candidate grid is sent randomly replacing the user’s original position to satisfy k-anonymization. Experimental results show that the proposed algorithm can better improve the quality of location services and the success rate of anonymous regions, which reduce the query time and storage space.