空间矢量数据细粒度强制查询访问控制模型及其高效实现

摘要

针对敏感空间地理矢量数据形状不规则、跨多级敏感区域分布的特点,对传统的强制访问控制模型进行空间扩展,提出了一种细粒度的空间矢量数据强制查询访问控制模型SV MAC(spatial vector data mandatory access control model).并进一步将空间数据查询与安全策略检索相结合,提出了一种AR+树(access R+树)索引结构,以在空间矢量数据查询过程中高效地实现SV MAC授权判定.实验结果表明,AR+树在为空间矢量数据的检索提供不可绕过的细粒度安全防护的同时,保障了前台响应速率和用户体验.%To protect the spatial vector data, which is often in an irregular shape and distributed throughout multiple sensitive areas, the traditional mandatory access control model is extended and explained in this paper. This paper also proposes a fine-grained spatial mandatory query access control model-SVMAC (spatial vector data mandatory access control model). Also, an AR+ spatial index tree technique is advanced, which combines the search of both spatial data and access control policies together to efficiently enforce the SVMAC model in the course of spatial vector data searching. Experiment results shows that AR+ tree can not only provide fine-grained security protection for sensitive spatial vector data, but can also guarantee good user experience for GIS (geography information system) applications.