A similarity evaluation algorithm and its application in multi-keyword search on encrypted cloud data

Searchable symmetric encryption (SSE), known as privacy-preserving keyword search, allows users to perform keyword search on encrypted data. However, until now there are no practical SSE schemes which can support query-document similarity evaluation and provide top-k retrieval on encrypted cloud data. This problem slows down the process of SSE schemes´ application in cloud storage service. In this paper, we propose a server-side similarity evaluation algorithm to realize the sorted search functionality. Based on this, we further propose an entire SSE solution to achieve the goal of privacy-preserving multi-keyword dynamic sorted (MKDS) search functionalities which steps closer to practical deployment. We formally demonstrate the security of our scheme and evaluate the practical performance of our scheme on the real-world dataset.