Fuzzy keyword search on encrypted cloud storage data with small index

Abstract

To ensure that the data can be stored in the cloud securely, people encrypt their data before outsourcing to the cloud, which makes searching on a large amount of encrypted data become a demanding task. Traditional searchable encryption schemes provide a range of approaches to search on encrypted data, but they only support exact keyword search. Exact keyword search is not suitable for cloud storage systems, because it doesn't allow users making any spelling errors or format inconsistencies, which greatly reduce the system usability. To the best of our knowledge, the relatively most feasible scheme published so far which supports fuzzy keyword search is the “Wildcard-based Fuzzy Set Construction” (INFOCOM 2010), in which each keyword is corresponding with O(l <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</sup> ) fuzzy keywords when the keyword length is l and the edit distance is d. In this paper we present the “Dictionary-based Fuzzy Set Construction”, in which each keyword is corresponding with much less fuzzy keywords. This improvement greatly reduces the index size, thereby reducing the storage and communication overheads. The experiment results show that when the number of keywords is 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> , the index size ratio between ours and theirs is 1:3.4(d = 1) and 1: 20.4(d = 2).