Efficient Dynamic Provable Data Possession from Dynamic Binary Tree

2016 ◽  
pp. 101-111 ◽  
Author(s):  
Changfeng Li ◽  
Huaqun Wang
Keyword(s):  
Binary Tree ◽  
Provable Data Possession

Seamless terrain rendering method based on binary tree and GPU

2013 ◽  
Vol 32 (9) ◽  
pp. 2548-2552
Author(s):  
Wei CAO ◽  
Guang-yao DUAN
Keyword(s):  
Binary Tree ◽  
Terrain Rendering

scholarly journals Efficient Searchable Symmetric Encryption Supporting Dynamic Multikeyword Ranked Search

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Yu Zhang ◽  
Yin Li ◽  
Yifan Wang
Keyword(s):  
Binary Tree ◽  
Search Time ◽  
Symmetric Encryption ◽  
Time Cost ◽  
Computational Costs ◽  
Related Space ◽  
Insertion And Deletion ◽  
Searchable Symmetric Encryption ◽  
Ranked Search ◽  
Binary Tree Structure

Searchable symmetric encryption that supports dynamic multikeyword ranked search (SSE-DMKRS) has been intensively studied during recent years. Such a scheme allows data users to dynamically update documents and retrieve the most wanted documents efficiently. Previous schemes suffer from high computational costs since the time and space complexities of these schemes are linear with the size of the dictionary generated from the dataset. In this paper, by utilizing a shallow neural network model called “Word2vec” together with a balanced binary tree structure, we propose a highly efficient SSE-DMKRS scheme. The “Word2vec” tool can effectively convert the documents and queries into a group of vectors whose dimensions are much smaller than the size of the dictionary. As a result, we can significantly reduce the related space and time cost. Moreover, with the use of the tree-based index, our scheme can achieve a sublinear search time and support dynamic operations like insertion and deletion. Both theoretical and experimental analyses demonstrate that the efficiency of our scheme surpasses any other schemes of the same kind, so that it has a wide application prospect in the real world.

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