Fast Privacy-Preserving Keyword Search on Encrypted Outsourced Data

被引:10
|
作者
Wodi, Bryan H. [1 ]
Leung, Carson K. [1 ]
Cuzzocrea, Alfredo [2 ]
Ourav, S. [1 ]
机构
[1] Univ Manitoba, Dept Comp Sci, Winnipeg, MB, Canada
[2] Univ Calabria, iDEA Lab, Arcavacata Di Rende, CS, Italy
基金
加拿大自然科学与工程研究理事会;
关键词
big data; data privacy; security; encryption; privacy-preserving; keyword search; information retrieval;
D O I
10.1109/bigdata47090.2019.9046058
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Cloud providers offer storage as a service to the data owners to store emails and files on the cloud server. However, sensitive data should be encrypted before storing on the cloud server to avoid privacy concerns. With the encryption of documents, it is not feasible for data owners to retrieve documents based on keyword search as they can do with plain text documents. Hence, it is desirable to perform a multi-keyword search on encrypted data. To achieve this goal, we present a fast privacy-preserving model for keyword search on encrypted outsourced data in this paper. Specifically, the model first performs a keyword search on encrypted data and checks its support for dynamic operations. Based on keyword search results, it then sorts all the relevant data documents using the number of keywords matched for a given query. To evaluate its performance of our model, we applied the standard metrics like precision and recall. The results show the effectiveness of our privacy-preserving keyword search on encrypted outsourced data.
引用
收藏
页数:10
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