An Efficient Semantic Aware Search Method over Encrypted Cloud Data

Abstract

With the increasing adoption of cloud computing, a growing number of users outsource their to cloud. To preserve the privacy, they are usually encrypted before outsourcing. However, the common practice of encryption makes the effective utilization of the data difficult. For example, it is difficult to search the given keywords in encrypted. Many schemes are proposed to make encrypted data searchable based on keywords. However, keyword-based search schemes ignore the semantic representation information of user’s retrieval, and cannot completely meet with users search intention. Therefore, how to design a content-based search scheme and make semantic search more effective and context-aware is a difficult challenge. In this paper, we propose ECSED, a novel semantic search scheme based on the concept hierarchy and the semantic relationship between concepts in the encrypted. ECSED uses two cloud servers. One is used to store the outsourced and return the ranked results to data users. The other one is used to compute the similarity scores between the documents and the query and send the scores to the first server. To further improve the search efficiency, we utilize a tree-based index structure to organize all the document index vectors. We employ the ranked search over encrypted cloud data as our basic frame to propose two secure schemes. The experiment results based on the real world show that the scheme is more efficient than previous schemes. We also prove that our schemes are secure under the known model and the known background model.