Abstract: In the era of big data, more and more users or enterprises upload a large amount of data to cloud storage so as to reduce the pressure of local storage and obtain efficient management of data sharing services. As a result, searchable encryption technology arises at the right moment. Retrievable efficiency and guarantee of data security have always been the focus of research. Therefore, a fast dimensionality reduction sorting search method based on feature matching (DRFM) is proposed. Through the proposed feature score algorithm, the index feature vector of each document is created; through the proposed matching score algorithm, the query matching vector of query keywords is created. The K-L transform algorithm is used to reduce the dimensions of all document index feature vectors and query matching vectors to improve the efficiency of the algorithm. Theoretical analysis and experimental results show that the proposed scheme is efficient and feasible.

Key words: feature matching, encryption, dimensionality reduction, indexed feature vector, query matching vector