A Secure and Dynamic Multi-Keyword Ranked Search Scheme over Encrypted Cloud Data
Due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their
data to cloud servers for great convenience and reduced cost in data management. However, sensitive data should be
encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document
retrieval. In this paper, we present a secure multi-keyword ranked search scheme over encrypted cloud data, which
simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space
model and the widely-used TF IDF model are combined in the index construction and query generation. We construct a
special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword
ranked search. The secure kNN algorithm is utilized to encrypt the index and query vectors, and meanwhile ensure accurate
relevance score calculation between encrypted index and query vectors. In order to resist statistical attacks, phantom terms
are added to the index vector for blinding search results. Due to the use of our special tree-based index structure, the
proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly.
Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.
Index Terms - Searchable encryption, multi-keyword ranked search, dynamic update, cloud computing.