Semantic-aware Searching Over Encrypted Data For Cloud Computing

Semantic-aware searching over Encrypted Data for Cloud Computing

Abstract:

With the increasing adoption of cloud computing, a growing number of users outsource their datasets to cloud. To preserve the privacy, the datasets are usually encrypted before outsourcing. To design a content-based search scheme and make semantic search more effective and context-aware is a dif?cult challenge. In this project, we propose ECSED, a novel semantic search scheme based on the concept hierarchy and the semantic relationship between concepts in the encrypted datasets. ECSED uses two cloud servers. One is used to store the outsourced datasets 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 ?rst server. To further improve the search ef?ciency, we utilize a tree-based index structure to organize all the document index vectors. We employ the multi keyword ranked search over encrypted cloud data as our basic frame to propose two secure schemes. The experiment results based on the real world datasets show that the scheme is more ef?cient than previous schemes. We also prove that our schemes are secure under the known ciphertext model and the known background model.