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논문검색

Research on MR-Tree Spatial Query Authenticated Index Introduced Neighbor Relationship

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

Abstract
 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

저자정보

  • Xiaofu Wei Department of Information Engineering, Logistical Engineering University, Chongqing, China
  • Shenglin Li Department of Information Engineering, Logistical Engineering University, Chongqing, China
  • Zuofei Tan Department of Information Engineering, Logistical Engineering University, Chongqing, China
  • Kaiwen Luo Department of Information Engineering, Logistical Engineering University, Chongqing, China
  • San Zhang Department of Information Engineering, Logistical Engineering University, Chongqing, China

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