Due to the increasing quality of cloud computing, additional and additional data homeowners are motivated to supply their data to cloud servers for nice convenience and reduced worth in data management. However, sensitive data got to be encrypted before outsourcing for privacy wants, that obsoletes data utilization like keyword-based document retrieval. throughout this paper, we tend to gift a secure multi-keyword stratified search theme over encrypted cloud data, that at a similar time supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and so the widely-used TFIDF model square measure combined within the index construction and question generation. we tend to construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to supply economical multi-keyword stratified search. The secure kNN algorithm is utilized to cipher the index and question vectors, and within the meanwhile guarantee correct association score calculation between encrypted index and question vectors. therefore on resist applied mathematics attacks, phantom terms square measure extra to the index vector for bright search results . due to the use of our special tree-based index structure, the planned theme will do sub-linear search time and upset the deletion and insertion of documents flexibly. extensive experiments are conducted to demonstrate the efficiency of the planned theme
Article Details
Unique Paper ID: 145713
Publication Volume & Issue: Volume 4, Issue 11
Page(s): 55 - 57
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