Enabling Secure and Efficient Multi-Keyword Ranked Search Scheme

Abstract-With increasing popularity of cloud computing, the data owners outsource their sensitive data to cloud servers for flexibility and reduced cost in data management. To protect data privacy the sensitive data should be encrypted by the data owner before outsourcing which obsoletes data utilization like keyword-based document retrieval. It is essential to develop an efficient and reliable cipher text search techniques, so that data owners can easily access and update cloud data. In this paper, we present a secure multi-keyword ranked search scheme over encrypted cloud data, which supports both multi-keyword ranked search and dynamic update. We have used the vector space model and the widely-used TF_IDF models are combined in the index construction and query generation. To improve search efficiency, we design tree based index structure which supports insertion and deletion update well without privacy leakage. To encrypt the indexes and query vectors the secure KNN algorithm is used. To calculates relevance score between encrypted index and query vectors our system is efficient. Our scheme achieves optimal search efficiency. Our scheme also reduces communication overhead. Hence the analysis shows security and efficiency of our scheme.