MinHash-Based Fuzzy Keyword Search of Encrypted Data across Multiple Cloud Servers

Jingsha He, Jianan Wu, Nafei Zhu and Muhammad Salman Pathan
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Jingsha He: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Jianan Wu: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Nafei Zhu: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
Muhammad Salman Pathan: Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China

Future Internet, 2018, vol. 10, issue 5, 1-18

Abstract: To enhance the efficiency of data searching, most data owners store their data files in different cloud servers in the form of cipher-text. Thus, efficient search using fuzzy keywords becomes a critical issue in such a cloud computing environment. This paper proposes a method that aims at improving the efficiency of cipher-text retrieval and lowering storage overhead for fuzzy keyword search. In contrast to traditional approaches, the proposed method can reduce the complexity of Min-Hash-based fuzzy keyword search by using Min-Hash fingerprints to avoid the need to construct the fuzzy keyword set. The method will utilize Jaccard similarity to rank the results of retrieval, thus reducing the amount of calculation for similarity and saving a lot of time and space overhead. The method will also take consideration of multiple user queries through re-encryption technology and update user permissions dynamically. Security analysis demonstrates that the method can provide better privacy preservation and experimental results show that efficiency of cipher-text using the proposed method can improve the retrieval time and lower storage overhead as well.

Keywords: cloud storage; multi-server; multi-user; fuzzy keyword search (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2018
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