| With the rapid development of cloud computing, more and more data and information are being centralized into cloud service provider (CSP). Although cloud services bring great convenience to the users, its reliability and security are extremely concerned by cloud users. In order to protect data privacy, sensitive data has to be encrypted before outsourcing to CSP, which makes searching keywords on encrypted cloud data to be a very challenge task.According to characteristics of cloud computing, we propose an efficient privacy-preserving approach to support multi-keyword search over encrypted data (short for PPMKS) on cloud storage. We assume that CSP is honest-but-curious and is considered as a potential attacker. In our PPMKS, the data owner will bind some keywords for each file, then the files and corresponding keywords have to be encrypted before sending to CSP. The CSP will construct a balanced binary sort tree based on the encrypted keywords for multiply-keyword search service. For those enterprise users who have their own internal cloud, the constructed balanced binary tree will be stored in their own internal cloud server, and the encrypted files are outsourced to CSP.PPMKS can only support exact keywords search. That’s to say, there is no tolerance of minor typos and format inconsistencies for keywords. For this evident shortcoming, we make an improvement, and propose an efficient scheme to support fuzzy keywords search over encrypted data (short for PPFKS). PPFKS uses a dictionary to construct a fuzzy set for each keyword. The cloud users can search their interesting files over CSP according the fuzzy set corresponding to the inputted extract keywords. Compared to the traditional scheme which uses wildcard-based technique to construct fuzzy sets, our scheme can reduce much burden over CSP.In our proposed scheme, authorized users can easily search encrypted files on cloud storage, which can make users enjoy the service of multi-keyword search and fuzzy-keyword search over encrypted data on cloud storage anytime and anywhere. |