Privacy Preserving Multi-Keyword Ranked Search over Encrypted Cloud Data

Multi-keyword ranked search over encrypted cloud data (MRSE) while preserving strict system-wise privacy in cloud computing paradigm. 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. Specifically, we use “inner product similarity�, i.e., the number of query keywords appearing in a document, to quantitatively evaluate the similarity of that document to the search query in “coordinate matching� principle. However, directly outsourcing data vector or query vector will violate index privacy or search privacy. To meet the challenge of supporting such multi-keyword semantic without privacy breaches, we propose a basic MRSE scheme using secure inner product computation, which is adapted from a secure k-nearest neighbor (kNN) technique, and then improve it step by step to achieve various privacy requirements.