Research on a Cipher-Text Fuzzy Retrieval Algorithm Based on Spatial Model

DOI

10.2991/cecs-18.2018.47How to use a DOI?

Keywords

cloud storage cipher-text retrieval multiple keywords fuzzy retrieval.

Abstract

with the development of the Internet, cloud computing and cloud storage are more and more widely used. Users are starting to store more and more large data files on cloud servers. In the cloud storage mode, some private data and sensitive data of users may be leaked. To protect data security, users need to encrypt their private data before storing it in the cloud server. However, when viewing the data, the user needs to restore the encrypted data, and then go back to the original search, which is a waste of time. Therefore, it is of great significance to study how to effectively and quickly realize cipher-text data retrieval [1]. When the data scale is large, the traditional retrieval structure is often inefficient and inaccurate. Therefore, how to ensure the security of cipher-text retrieval and how to improve the efficiency and accuracy of keyword fuzzy retrieval has become the focus of experts and scholars. Because of the low efficiency of cipher-text retrieval, combined with the current cipher-text retrieval scheme, a fuzzy retrieval method for cipher-text with multiple key words is proposed. This method is aimed at cipher-text retrieval, which realizes fuzzy retrieval of multiple keywords. In addition, it can also resist the trap door association attack, adaptive keyword selection attack and similarity attack.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yuhua Wei
PY  - 2018/07
DA  - 2018/07
TI  - Research on a Cipher-Text Fuzzy Retrieval Algorithm Based on Spatial Model
BT  - Proceedings of the 2018 International Symposium on Communication Engineering & Computer Science (CECS 2018)
PB  - Atlantis Press
SP  - 273
EP  - 277
SN  - 2352-538X
UR  - https://doi.org/10.2991/cecs-18.2018.47
DO  - 10.2991/cecs-18.2018.47
ID  - Wei2018/07
ER  -