원문정보
초록
영어
In database outsourcing, the data owner delegates the tasks of data management to a third-party service provider. As the service provider may be untrusted or susceptible to attacks, query authentication is an essential part. Merkle R-tree (MR-tree) is one of the most efficient authenticated index that combines Merkle hash tree with R*-tree. MR-tree can provide an efficient range query authentication, however, as it uses the traditional R*-tree query structure in neighbor queries, a large number of unnecessary nodes may be accessed, and that can affect the efficiency of the query. In this paper, the neighbor relationship is introduced into the construction of MR-tree, and we propose a new index structure, called VMR-tree that incorporates the Voronoi diagram into MR-tree. In order to utilize VMR-tree index structure, we propose algorithms for spatial nearest neighbor queries and experiments to verify it has a better efficiency in spatial neighbor query authentication.
목차
1. Introduction
2. Background
2.1. Outsourced Spatial Database Query Authentication
2.2. Voronoi Diagram
3. VMR-Tree Query Authenticated Index
3.1. Structure of VMR-Tree
3.2. kNN Query Authentication
4. Experimental Evaluation
5. Conclusions
References