精度可控的矢量地理数据脱密方法  

A precision alterable declassification technique for vector geo-data

作　　者：李安波[1,2] 吴雪荣[1] 解宪丽[3] 周卫[1,2] LI Anbo WU Xuerong XIE Xianli ZHOU Wei(Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing, Jiangsu 210023, China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, Jiangsu 210023, China Institute of Soil Science, Chinese Academy of Sciences, Nanjing, Jiangsu 210008, China)

机构地区：[1]南京师范大学虚拟地理环境教育部重点实验室,江苏南京210023 [2]江苏省地理信息资源开发与利用协同创新中心,江苏南京210023 [3]中国科学院南京土壤研究所,江苏南京210008

出　　处：《中国矿业大学学报》2016年第5期1050-1057,共8页Journal of China University of Mining & Technology

基　　金：国家自然科学基金项目(41371374;41471175);国家社会科学基金重大项目(11&ZD162)

摘　　要：采用基于Logistic混沌系统的干扰脱密方法和基于辅助点的精度控制方法,实现了精度可控的矢量地理数据脱密处理;脱密后数据经过坐标还原、辅助点识别和剔除等处理,可实现脱密数据的无损还原.通过探讨基于图形复杂度的图形形态相似性评价方法、基于四交集模型的空间拓扑关系评价方法和基于不同邻接点间局部方向关系的空间方向关系一致性评价方法,提供了定量化的脱密算法性能评价手段.实验表明:本脱密方法能够进行有效的精度控制,且具有较好的干扰随机性和自动化特性.实验数据脱密前后,其在图形形态、空间拓扑关系和空间方向关系等方面的一致性分别达到了98.93%,99.71%和99.20%.算法特性基本满足了矢量地理数据在数据公开、安全传输、封装存储等方面的应用需求.In this paper, we developed a technique of information declassification and reversion which is applicable for vector geo-data in GIS. Firstly, for information declassification, a set of interfering points were created using logistic chaotic system. Then, to control the extent of in- formation interfering, some auxiliary points were inserted by user-defined step. Finally, after the process of coordinate reversion, the recognition and elimination of auxiliary points, the data can be restored to original state. To evaluate the effects of this method, we assess the consistency of shape patterns by graphic complexity, the consistency of topological spatial relation- ships based on 4-intersection model,and the consistency of spatial directional relationships by local directional relationships of adjacent points. This technique implements information declassification according to the precision that user demands with stochastic interference and better automation, and enables the consistency of shape patterns （98. 93%）, spatial topology relationships （99.71%） and spatial directional relationships （99.20%） before and after declassification. It can meet the declassification requirements of vector geo-data for the applications such as data sharing, secure transmission, and sealed storage.

关 键 词：矢量地理数据 脱密 精度控制 可逆变换 涉密地理数据 

分 类 号：P28[天文地球—地图制图学与地理信息工程]