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.
Highlights
With the advancement of cloud computing, more and more enterprises and individuals choose the option of storing their data in cloud servers to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources as well as to reduce the burden of managing their own storage
We propose a fuzzy keyword search scheme for the scenarios of multiple servers and multiple users that has the property of preserving security and privacy of data
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Summary
With the advancement of cloud computing, more and more enterprises and individuals choose the option of storing their data in cloud servers to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources as well as to reduce the burden of managing their own storage. For the retrieval of cipher-text files, a lot of research has been done on fuzzy keyword search over encrypted data in the cloud. To find the most similar keywords, both schemes need to construct a fuzzy keyword set, which incurs heavy computation load and communication overhead, and costs a large amount of storage space in the cloud servers These schemes can only sort the search results by editing distance with rough results without being able to return accurate search results. We propose a fuzzy keyword search scheme for the scenarios of multiple servers and multiple users that has the property of preserving security and privacy of data.
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