【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.更多还原

【Abstract】 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 information 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 relationships 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 declassifi-cation.It can meet the declassification requirements of vector geo-data for the applications such as data sharing,secure transmission,and sealed storage.更多还原