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Privacy-Preserving Multi-keyword Ranked Search over Encrypted Cloud Data
| Content Provider | Semantic Scholar |
|---|---|
| Author | Vishvapathi, P. Reddy, M. J. |
| Abstract | The advent of cloud computing, data owners are motivated to outsource their complex data management systems from local sites to commercial public cloud for great flexibility and economic savings. But for protecting data privacy, sensitive data has to be encrypted before outsourcing, which obsoletes traditional data utilization based on plaintext keyword search. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in cloud, it is crucial for the search service to allow multi-keyword query and provide result similarity ranking to meet the effective data retrieval need. Related works on searchable encryption focus on single keyword search or Boolean keyword search, and rarely differentiate the search results. In this paper, for the first time, we define and solve the challenging problem of privacy-preserving multi-keyword ranked search over encrypted cloud data (MRSE), and establish a set of strict privacy requirements for such a secure cloud data utilization system to become a reality. Among various multi-keyword semantics, we choose the efficient principle of " coordinate matching " , i.e., as many matches as possible, to capture the similarity between search query and data documents, and further use " inner product similarity " to quantitatively formalize such principle for similarity measurement. We first propose a basic MRSE scheme using secure inner product computation, and then significantly improve it to meet different privacy requirements in two levels of threat models. Thorough analysis investigating privacy and efficiency guarantees of proposed schemes is given, and experiments on the real-world dataset further show proposed schemes indeed introduce low overhead on computation and communication. INTRODUCTION Due to the rapid expansion of data, the data owners tend to store their data into the cloud to release the burden of data storage and maintenance [1]. However, as the cloud customers and the cloud server are not in the same trusted domain, our outsourced data may be under the exposure to the risk. Thus, before sent to the cloud, the sensitive data needs to be encrypted to protect for data privacy and combat unsolicited accesses. Unfortunately, the traditional plaintext search methods cannot be directly applied to the encrypted cloud data any more. The traditional information retrieval (IR) has already provided multi-keyword ranked search for the data user. In the same way, the cloud server needs provide the data user with the similar function, while protecting data and search privacy. It … |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ijera.com/special_issue/NCDATES/CSE/PART-3/CSE%20134-2528.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
